Pleiotropic effects of a rel mutation on stress survival of Rhizobium etli CNPAF512

Braeken, Kristien; Fauvart, Maarten; Vercruysse, Maarten; Beullens, Serge; Lambrichts, Ivo; Michiels, Jan

doi:10.1186/1471-2180-8-219

Cited by 19 publications

(19 citation statements)

References 47 publications

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“…; Braeken et al. ). Based on a genome‐wide transcriptome analysis, stress response regulators involved in the (p)ppGpp‐dependent response were identified (Vercruysse et al.…”

Section: Introductionmentioning

confidence: 98%

Canonical and non‐canonical EcfG sigma factors control the general stress response in Rhizobium etli

et al. 2013

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A core component of the α-proteobacterial general stress response (GSR) is the extracytoplasmic function (ECF) sigma factor EcfG, exclusively present in this taxonomic class. Half of the completed α-proteobacterial genome sequences contain two or more copies of genes encoding σEcfG-like sigma factors, with the primary copy typically located adjacent to genes coding for a cognate anti-sigma factor (NepR) and two-component response regulator (PhyR). So far, the widespread occurrence of additional, non-canonical σEcfG copies has not satisfactorily been explained. This study explores the hierarchical relation between Rhizobium etli σEcfG1 and σEcfG2, canonical and non-canonical σEcfG proteins, respectively. Contrary to reports in other species, we find that σEcfG1 and σEcfG2 act in parallel, as nodes of a complex regulatory network, rather than in series, as elements of a linear regulatory cascade. We demonstrate that both sigma factors control unique yet also shared target genes, corroborating phenotypic evidence. σEcfG1 drives expression of rpoH2, explaining the increased heat sensitivity of an ecfG1 mutant, while katG is under control of σEcfG2, accounting for reduced oxidative stress resistance of an ecfG2 mutant. We also identify non-coding RNA genes as novel σEcfG targets. We propose a modified model for GSR regulation in R. etli, in which σEcfG1 and σEcfG2 function largely independently. Based on a phylogenetic analysis and considering the prevalence of α-proteobacterial genomes with multiple σEcfG copies, this model may also be applicable to numerous other species.

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“…; Braeken et al. ). Based on a genome‐wide transcriptome analysis, stress response regulators involved in the (p)ppGpp‐dependent response were identified (Vercruysse et al.…”

Section: Introductionmentioning

confidence: 98%

Canonical and non‐canonical EcfG sigma factors control the general stress response in Rhizobium etli

et al. 2013

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“…For example, an R. etli relA mutant fails to switch to a coccoid form, a morphology typical of WT nodule-residing bacteroids (25). Nodules produced in the host P. vulgaris by an R. etli relA mutant are smaller than those produced by the WT strain (39).…”

Section: Plant Pathogens and Symbiontsmentioning

confidence: 99%

“…These symbiotic bacteria are exposed to challenges such as high salinity and transient nutrient availability both prior to infection and during nodulation. In R. etli and S. meliloti, the bifunctional synthetase/ hydrolase homologue, termed RelA, affects salt tolerance (25,211). Furthermore, relA contributes to R. etli survival of heat shock, peroxide stress, and minimal medium (25) as well as nutritional competence (39).…”

Section: Plant Pathogens and Symbiontsmentioning

confidence: 99%

ppGpp Conjures Bacterial Virulence

Dalebroux

Svensson

Gaynor

et al. 2010

Microbiol Mol Biol Rev

328

364

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SUMMARY Like for all microbes, the goal of every pathogen is to survive and replicate. However, to overcome the formidable defenses of their hosts, pathogens are also endowed with traits commonly associated with virulence, such as surface attachment, cell or tissue invasion, and transmission. Numerous pathogens couple their specific virulence pathways with more general adaptations, like stress resistance, by integrating dedicated regulators with global signaling networks. In particular, many of nature's most dreaded bacteria rely on nucleotide alarmones to cue metabolic disturbances and coordinate survival and virulence programs. Here we discuss how components of the stringent response contribute to the virulence of a wide variety of pathogenic bacteria.

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“…Thus, we hypothesized that proline catabolism may account for the differences in oxidative stress resistance observed between strains CSH4 and JT31. Although the CSH4 and JT31 strains are commonly used for proline studies (4,5,9), the CSH4 strain contains mutations in relA and spoT, which regulate (p)ppGpp levels and are important for bacterial survival under nutrient starvation and oxidative and osmotic stress conditions (38,39). Thus, to further evaluate the effects of proline metabolism on oxidative stress sensitivity, a ⌬putA strain of MG1655 was generated by P1 transduction (Fig.…”

Section: E Coli Puta Mutants Have Increased Oxidative Stress Sensitimentioning

confidence: 99%

Proline Metabolism IncreaseskatGExpression and Oxidative Stress Resistance in Escherichia coli

2014

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The oxidation of L-proline to glutamate in Gram-negative bacteria is catalyzed by the proline utilization A (PutA) flavoenzyme, which contains proline dehydrogenase (PRODH) and ⌬ 1 -pyrroline-5-carboxylate (P5C) dehydrogenase domains in a single polypeptide. Previous studies have suggested that aside from providing energy, proline metabolism influences oxidative stress resistance in different organisms. To explore this potential role and the mechanism, we characterized the oxidative stress resistance of wild-type and putA mutant strains of Escherichia coli. Initial stress assays revealed that the putA mutant strain was significantly more sensitive to oxidative stress than the parental wild-type strain. Expression of PutA in the putA mutant strain restored oxidative stress resistance, confirming that depletion of PutA was responsible for the oxidative stress phenotype. Treatment of wild-type cells with proline significantly increased hydroperoxidase I (encoded by katG) expression and activity. Furthermore, the ⌬katG strain failed to respond to proline, indicating a critical role for hydroperoxidase I in the mechanism of proline protection. The global regulator OxyR activates the expression of katG along with several other genes involved in oxidative stress defense. In addition to katG, proline increased the expression of grxA (glutaredoxin 1) and trxC (thioredoxin 2) of the OxyR regulon, implicating OxyR in proline protection. Proline oxidative metabolism was shown to generate hydrogen peroxide, indicating that proline increases oxidative stress tolerance in E. coli via a preadaptive effect involving endogenous hydrogen peroxide production and enhanced catalase-peroxidase activity.T he conversion of L-proline to glutamate is a four-electron oxidation process that is coordinated in two successive steps by the enzymes proline dehydrogenase (PRODH) and ⌬ 1 -pyrroline-5-carboxylate dehydrogenase (P5CDH) (Fig. 1) (1). In eukaryotes, PRODH and P5CDH are separately encoded enzymes localized in the mitochondrion. In Gram-negative bacteria, PRODH and P5CDH are combined into a bifunctional enzyme known as proline utilization A (PutA) (1, 2). The PRODH domain contains a noncovalently bound flavin adenine dinucleotide (FAD) cofactor and couples the two-electron oxidation of proline to the reduction of ubiquinone in the cytoplasmic membrane (3). The product of the PRODH reaction, ⌬ 1 -pyrroline-5-carboxylate (P5C), is subsequently hydrolyzed to glutamate-␥-semialdehyde (GSA), which is then oxidized to glutamate by the NAD ϩ -dependent P5CDH domain (2). In certain Gram-negative bacteria such as Escherichia coli, PutA also has an N-terminal ribbon-helix-helix (RHH) DNA-binding domain (residues 1 to 47) (4). The RHH domain enables PutA to act as an autogenous transcriptional regulator of the putA and putP (highaffinity Na ϩ -proline transporter) genes (4). PutA represses put gene expression by binding to five operator sites in the put regulatory region (5). Transcription of the put genes is activated by proline, which causes a r...

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Pleiotropic effects of a rel mutation on stress survival of Rhizobium etli CNPAF512

Cited by 19 publications

References 47 publications

Canonical and non‐canonical EcfG sigma factors control the general stress response in Rhizobium etli

Canonical and non‐canonical EcfG sigma factors control the general stress response in Rhizobium etli

ppGpp Conjures Bacterial Virulence

Proline Metabolism IncreaseskatGExpression and Oxidative Stress Resistance in Escherichia coli

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