Regulatory Feedback Loop of Two phz Gene Clusters through 5′-Untranslated Regions in Pseudomonas sp. M18

BACKGROUND: Phenazines are important compounds produced by pseudomonads and other bacteria. Two phz gene clusters called phzA1-G1 and phzA2-G2, respectively, were found in the genome of Pseudomonas sp. M18, an effective biocontrol agent, which is highly homologous to the opportunistic human pathogen P. aeruginosa PAO1, however little is known about the correlation between the expressions of two phz gene clusters. METHODOLOGY/PRINCIPAL FINDINGS: Two chromosomal insertion inactivated mutants for the two gene clusters were constructed respectively and the correlation between the expressions of two phz gene clusters was investigated in strain M18. Phenazine-1-carboxylic acid (PCA) molecules produced from phzA2-G2 gene cluster are able to auto-regulate expression itself and activate the expression of phzA1-G1 gene cluster in a circulated amplification pattern. However, the post-transcriptional expression of phzA1-G1 transcript was blocked principally through 5'-untranslated region (UTR). In contrast, the phzA2-G2 gene cluster was transcribed to a lesser extent and translated efficiently and was negatively regulated by the GacA signal transduction pathway, mainly at a post-transcriptional level. CONCLUSIONS/SIGNIFICANCE: A single molecule, PCA, produced in different quantities by the two phz gene clusters acted as the functional mediator and the two phz gene clusters developed a specific regulatory mechanism which acts through 5'-UTR to transfer a single, but complex bacterial signaling event in Pseudomonas sp. strain M18

Rhamnolipids: diversity of structures, microbial origins and roles

Rhamnolipids are glycolipidic biosurfactants produced by various bacterial species. They were initially found as exoproducts of the opportunistic pathogen Pseudomonas aeruginosa and described as a mixture of four congeners: α-L-rhamnopyranosyl-α-L-rhamnopyranosyl-β-hydroxydecanoyl-β-hydroxydecanoate (Rha-Rha-C10-C10), α-L-rhamnopyranosyl-α-L-rhamnopyranosyl-β-hydroxydecanoate (Rha-Rha-C10), as well as their mono-rhamnolipid congeners Rha-C10-C10 and Rha-C10. The development of more sensitive analytical techniques has lead to the further discovery of a wide diversity of rhamnolipid congeners and homologues (about 60) that are produced at different concentrations by various Pseudomonas species and by bacteria belonging to other families, classes, or even phyla. For example, various Burkholderia species have been shown to produce rhamnolipids that have longer alkyl chains than those produced by P. aeruginosa. In P. aeruginosa, three genes, carried on two distinct operons, code for the enzymes responsible for the final steps of rhamnolipid synthesis: one operon carries the rhlAB genes and the other rhlC. Genes highly similar to rhlA, rhlB, and rhlC have also been found in various Burkholderia species but grouped within one putative operon, and they have been shown to be required for rhamnolipid production as well. The exact physiological function of these secondary metabolites is still unclear. Most identified activities are derived from the surface activity, wetting ability, detergency, and other amphipathic-related properties of these molecules. Indeed, rhamnolipids promote the uptake and biodegradation of poorly soluble substrates, act as immune modulators and virulence factors, have antimicrobial activities, and are involved in surface motility and in bacterial biofilm development

A Complete Scheme for Short Range . . .

f# ## #6# shix"spsge"syx## feo/ooifsex# p'ewi#y'u## vie'xsxq# xi...'ev#xi"#y'uf##EDH##effygse"syx##y"swsfe"syx##wyhiv#we"grsxq# yggv...fsyx ### Ax"'yh...g"syx E want to identify armoured vehicles on short range infra-red images. Identification means that the precise type of the vehicle must be found. The resulting information is thus more precise than for detection or recognition. Indeed, for detection, vehicle potential locations are searched; for recognition the vehicle must be classified as member of a broad class as `armoured vehicle' or `aeroplane'. When the vehicle get closer to the camera, detection, recognition and identification are progressively possible for long, medium and short range images respectively. A typical image of our database is presented in figure 1. The image is taken at short range; many details are visible and identification should be possible. The major difficulties in the identification problem are due to the quality of t

ANOMALY DETECTION IN COMPLEX ENVIRONMENTS: EVALUATION OF THE INTER- AND INTRA-METHOD CONSISTENCY

Many anomaly detection methods, depending on various parameters, have been proposed in literature. Given the diversity of available anomaly detectors, from an operational viewpoint it is interesting to determine an efficient strategy to find the best suited detector for a given application. This is not obvious, especially in scenes with a highly structured background. The work presented here proposes a generic approach to the problem by examining the following questions: How different are the results of the various anomaly detectors? Are the parameters influencing the results significantly? Are there classes of methods sufficiently similar so that one can test only one of each class and see which results are most adequate for a given application? What are the spectral/spatial characteristics of the differences between methods? Can one predict which detector will give the best results for a given application? The current paper tries to answer the first three questions by comparing results of different types of anomaly detectors applied to different complex (urban, industrial and harbor) scenes. The comparison is not in absolute terms because it does not rely on a priori ground truth. In stead the detectors are compared relative to one another, the aim being to evaluate the similarities between the performance of the detectors and the dependency of their results on the used parameters, i.e. the inter- and intra method consistency. Index Terms — Anomaly detection, hyperspectral, clustering, segmentatio