Chemical Analysis of Cellular and Extracellular Carbohydrates of a Biofilm-Forming Strain Pseudomonas aeruginosa PA14

Background: Pseudomonas aeruginosa is a Gram-negative bacterium and an opportunistic pathogen, which causes persisting life-threatening infections in cystic fibrosis (CF) patients. Biofilm mode of growth facilitates its survival in a variety of environments. Most P. aeruginosa isolates, including the non-mucoid laboratory strain PA14, are able to form a thick pellicle, which results in a surface-associated biofilm at the air-liquid (A\ufffdL) interface in standing liquid cultures. Exopolysaccharides (EPS) are considered as key components in the formation of this biofilm pellicle. In the non-mucoid P. aeruginosa strain PA14, the \ufffd\ufffdscaffolding\ufffd\ufffd polysaccharides of the biofilm matrix, and the molecules responsible for the structural integrity of rigid A\ufffdL biofilm have not been identified. Moreover, the role of LPS in this process is unclear, and the chemical structure of the LPS O-antigen of PA14 has not yet been elucidated. Principal Findings: In the present work we carried out a systematic analysis of cellular and extracellular (EC) carbohydrates of P. aeruginosa PA14. We also elucidated the chemical structure of the LPS O-antigen by chemical methods and 2-D NMR spectroscopy. Our results showed that it is composed of linear trisaccharide repeating units, identical to those described for P. aeruginosa Lanyi type O:2a,c (Lanyi-Bergman O-serogroup 10a, 10c; IATS serotype 19) and having the following structure: -4)-a-L-GalNAcA-(1\ufffd3)-a-D-QuiNAc-(1\ufffd3)- a-L-Rha-(1-. Furthermore, an EC O-antigen polysaccharide (EC O-PS) and the glycerol-phosphorylated cyclic b-(1,3)-glucans were identified in the culture supernatant of PA14, grown statically in minimal medium. Finally, the extracellular matrix of the thick biofilm formed at the A-L interface contained, in addition to eDNA, important quantities (at least ,20% of dry weight) of LPS-like material. Conclusions: We characterized the chemical structure of the LPS O-antigen and showed that the O-antigen polysaccharide is an abundant extracellular carbohydrate of PA14. We present evidence that LPS-like material is found as a component of a biofilm matrix of P. aeruginosa.Peer reviewed: YesNRC publication: Ye

Surface Hardness Impairment of Quorum Sensing and Swarming for Pseudomonas aeruginosa

The importance of rhamnolipid to swarming of the bacterium Pseudomonas aeruginosa is well established. It is frequently, but not exclusively, observed that P. aeruginosa swarms in tendril patterns—formation of these tendrils requires rhamnolipid. We were interested to explain the impact of surface changes on P. aeruginosa swarm tendril development. Here we report that P. aeruginosa quorum sensing and rhamnolipid production is impaired when growing on harder semi-solid surfaces. P. aeruginosa wild-type swarms showed huge variation in tendril formation with small deviations to the “standard” swarm agar concentration of 0.5%. These macroscopic differences correlated with microscopic investigation of cells close to the advancing swarm edge using fluorescent gene reporters. Tendril swarms showed significant rhlA-gfp reporter expression right up to the advancing edge of swarming cells while swarms without tendrils (grown on harder agar) showed no rhlA-gfp reporter expression near the advancing edge. This difference in rhamnolipid gene expression can be explained by the necessity of quorum sensing for rhamnolipid production. We provide evidence that harder surfaces seem to limit induction of quorum sensing genes near the advancing swarm edge and these localized effects were sufficient to explain the lack of tendril formation on hard agar. We were unable to artificially stimulate rhamnolipid tendril formation with added acyl-homoserine lactone signals or increasing the carbon nutrients. This suggests that quorum sensing on surfaces is controlled in a manner that is not solely population dependent

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

Séminaire des gestionnaires de la conservation de la biodiversité à La Réunion

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Constructing Regularity Feature Trees for Solid Models

Approximate geometric models, e.g. as created by reverse engineering, describe the approximate shape of an object, but do not record the underlying design intent. Automatically inferring geometric aspects of the design intent, represented by feature trees and geometric constraints, enhances the utility of such models for downstream tasks. One approach to design intent detection in such models is to decompose them into regularity features. Geometric regularities such as symmetries may then be sought in each regularity feature, and subsequently be combined into a global, consistent description of the model’s geometric design intent. This paper describes a systematic approach for finding such regularity features based on recovering broken symmetries in the model. The output is a tree of regularity features for subsequent use in regularity detection and selection. Experimental results are given to demonstrate the operation and efficiency of the algorithm