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Quorum sensing signaling molecules produced by reference and emerging soft-rot bacteria (Dickeya and Pectobacterium spp.).

ABSTRACT: BACKGROUND:Several small diffusible molecules are involved in bacterial quorum sensing and virulence. The production of autoinducers-1 and -2, quinolone, indole and ?-amino butyrate signaling molecules was investigated in a set of soft-rot bacteria belonging to six Dickeya or Pectobacterium species including recent or emerging potato isolates. METHODOLOGY/PRINCIPAL FINDINGS:Using bacterial biosensors, immunoassay, and chromatographic analysis, we showed that soft-rot bacteria have the common ability to produce transiently during their exponential phase of growth the N-3-oxo-hexanoyl- or the N-3-oxo-octanoyl-l-homoserine lactones and a molecule of the autoinducer-2 family. Dickeya spp. produced in addition the indole-3-acetic acid in tryptophan-rich conditions. All these signaling molecules have been identified for the first time in the novel Dickeya solani species. In contrast, quinolone and ?-amino butyrate signals were not identified and the corresponding synthases are not present in the available genomes of soft-rot bacteria. To determine if the variations of signal production according to growth phase could result from expression modifications of the corresponding synthase gene, the respective mRNA levels were estimated by reverse transcriptase-PCR. While the N-acyl-homoserine lactone production is systematically correlated to the synthase expression, that of the autoinducer-2 follows the expression of an enzyme upstream in the activated methyl cycle and providing its precursor, rather than the expression of its own synthase. CONCLUSIONS/SIGNIFICANCE:Despite sharing the S-adenosylmethionine precursor, no strong link was detected between the production kinetics or metabolic pathways of autoinducers-1 and -2. In contrast, the signaling pathway of autoinducer-2 seems to be switched off by the indole-3-acetic acid pathway under tryptophan control. It therefore appears that the two genera of soft-rot bacteria have similarities but also differences in the mechanisms of communication via the diffusible molecules. Our results designate autoinducer-1 lactones as the main targets for a global biocontrol of soft-rot bacteria communications, including those of emerging isolates.

SUBMITTER: Crepin A

PROVIDER: S-EPMC3335102 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Quorum sensing signaling molecules produced by reference and emerging soft-rot bacteria (Dickeya and Pectobacterium spp.).

Crépin Alexandre A Barbey Corinne C Beury-Cirou Amélie A Hélias Valérie V Taupin Laure L Reverchon Sylvie S Nasser William W Faure Denis D Dufour Alain A Orange Nicole N Feuilloley Marc M Heurlier Karin K Burini Jean-François JF Latour Xavier X

PloS one 20120423 4

<h4>Background</h4>Several small diffusible molecules are involved in bacterial quorum sensing and virulence. The production of autoinducers-1 and -2, quinolone, indole and γ-amino butyrate signaling molecules was investigated in a set of soft-rot bacteria belonging to six Dickeya or Pectobacterium species including recent or emerging potato isolates.<h4>Methodology/principal findings</h4>Using bacterial biosensors, immunoassay, and chromatographic analysis, we showed that soft-rot bacteria have ...[more]

PMID: 22539957

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Project description:Soft Rot Pectobacteriaceae (SRP; Pectobacterium spp. and Dickeya spp., formerly known as pectinolytic Erwinia spp.) are necrotrophic bacterial pathogens infecting a large number of plant species worldwide, including agriculturally-important crops. Despite the SRP importance in agriculture, little is known about the bacteriophages infecting them, and even less about the prophages present in their genomes. Prophages are recognized as factors underlying bacterial virulence, genomic diversification and ecological fitness that contribute to the novel phenotypic properties of bacterial hosts. Likewise, they are recognized as a driving force of bacterial evolution. In this study, 57 complete genomes of Pectobacterium spp. and Dickeya spp. deposited in NCBI GenBank, were analyzed for the presence of prophage-like elements. Viral sequences were discovered in 95% of bacterial genomes analyzed with the use of PHASTER, PhiSpy, and manual curation of the candidate sequences using NCBI BLAST. In total 37 seemingly intact and 48 putatively defective prophages were found. The 37 seemingly intact prophages (27 sequences in Dickeya spp. genomes and 10 sequences in Pectobacterium spp. genomes) were annotated using RAST. Analysis of the prophage genes encoding viral structural proteins allowed classification of these prophages into different families of the order Caudovirales (tailed bacteriophages) with the SRP prophages of the Myoviridae family (81% of found prophages) being the most abundant. The phylogenetic relationships between prophages were analyzed using amino acid sequences of terminase large subunit (gene terL), integrase (gene int), holin (gene hol), and lysin (gene lys). None of these markers however proved fully useful for clear phylogenetic separation of prophages of SRP into distinct clades. Comparative analyses of prophage proteomes revealed six clusters: five present in Dickeya spp. and one within Pectobacterium spp. When screened for the presence of bacterial genes in the genomes of intact prophages, only one prophage did not contain any ORFs of bacterial origin, the other prophages contained up to 23 genes acquired from bacterial hosts. The bacterial genes present in prophages could possibly affect fitness and virulence of their hosts. The implication of prophage presence in the genomes of Pectobacterium spp. and Dickeya spp. is discussed.

Project description:BACKGROUND: A wealth of genome sequences has provided thousands of genes of unknown function, but identification of functions for the large numbers of hypothetical genes in phytopathogens remains a challenge that impacts all research on plant-microbe interactions. Decades of research on the molecular basis of pathogenesis focused on a limited number of factors associated with long-known host-microbe interaction systems, providing limited direction into this challenge. Computational approaches to identify virulence genes often rely on two strategies: searching for sequence similarity to known host-microbe interaction factors from other organisms, and identifying islands of genes that discriminate between pathogens of one type and closely related non-pathogens or pathogens of a different type. The former is limited to known genes, excluding vast collections of genes of unknown function found in every genome. The latter lacks specificity, since many genes in genomic islands have little to do with host-interaction. RESULT: In this study, we developed a supervised machine learning approach that was designed to recognize patterns from large and disparate data types, in order to identify candidate host-microbe interaction factors. The soft rot Enterobacteriaceae strains Dickeya dadantii 3937 and Pectobacterium carotovorum WPP14 were used for development of this tool, because these pathogens are important on multiple high value crops in agriculture worldwide and more genomic and functional data is available for the Enterobacteriaceae than any other microbial family. Our approach achieved greater than 90% precision and a recall rate over 80% in 10-fold cross validation tests. CONCLUSION: Application of the learning scheme to the complete genome of these two organisms generated a list of roughly 200 candidates, many of which were previously not implicated in plant-microbe interaction and many of which are of completely unknown function. These lists provide new targets for experimental validation and further characterization, and our approach presents a promising pattern-learning scheme that can be generalized to create a resource to study host-microbe interactions in other bacterial phytopathogens.

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Dataset Information

Quorum sensing signaling molecules produced by reference and emerging soft-rot bacteria (Dickeya and Pectobacterium spp.).

Publications

Quorum sensing signaling molecules produced by reference and emerging soft-rot bacteria (Dickeya and Pectobacterium spp.).

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