Interference with the germination and growth ofUlvazoospores by quorum-sensing molecules fromUlva-associated epiphytic bacteria

Ulva zoospores preferentially settle on N-acylhomoserine lactone (AHL) producing marine bacterial biofilms. To investigate whether AHL signal molecules also affect the success and rate of zoospore germination in addition to zoospore attraction, the epiphytic bacteria associated with mature Ulva linza were characterized and bacterial isolates representative of this community tested for the ability to produce AHLs. Two of these AHL-producing isolates, Sulfitobacter spp. 376 and Shewanella spp. 79, were transformed with plasmids expressing the Bacillus spp. AHL lactonase gene aiiA to generate AHL-deficient variants. The germination and growth of U. linza zoospores was studied in the presence of these AHL-deficient strains and their AHL-producing counterparts. This revealed that the AHLs produced by Sulfitobacter spp. and Shewanella spp. or the bacterial products they regulate have a negative impact on both zoospore germination and the early growth of the Ulva germling. Further experiments with Escherichia coli biofilms expressing recombinant AHL synthases and synthetic AHLs provide data to demonstrate that zoospores germinated and grown in the absence of AHLs were significantly longer than those germinated in the presence of AHLs. These results reveal an additional role for AHLs per se in the interactive relationships between marine bacteria and Ulva zoospores.

Interference with the germination and growth of Ulvazoospores by quorum-sensing molecules from Ulva-associated epiphytic bacteria

Ulva zoospores preferentially settle on N-acylhomoserine lactone (AHL) producing marine bacterial biofilms. To investigate whether AHL signal molecules also affect the success and rate of zoospore germination in addition to zoospore attraction, the epiphytic bacteria associated with mature Ulva linza were characterized and bacterial isolates representative of this community tested for the ability to produce AHLs. Two of these AHL-producing isolates, Sulfitobacter spp. 376 and Shewanella spp. 79, were transformed with plasmids expressing the Bacillus spp. AHL lactonase gene aiiA to generate AHL-deficient variants. The germination and growth of U. linza zoospores was studied in the presence of these AHL-deficient strains and their AHL-producing counterparts. This revealed that the AHLs produced by Sulfitobacter spp. and Shewanella spp. or the bacterial products they regulate have a negative impact on both zoospore germination and the early growth of the Ulva germling. Further experiments with Escherichia coli biofilms expressing recombinant AHL synthases and synthetic AHLs provide data to demonstrate that zoospores germinated and grown in the absence of AHLs were significantly longer than those germinated in the presence of AHLs. These results reveal an additional role for AHLs per se in the interactive relationships between marine bacteria and Ulva zoospores.

Diverse profiles of N‐acyl‐homoserine lactone molecules found in cnidarians

Many marine habitats, such as the surface and tissues of marine invertebrates, including corals, harbour diverse populations of microorganisms, which are thought to play a role in the health of their hosts and influence mutualistic and competitive interactions. Investigating the presence and stability of quorum sensing (QS) in these ecosystems may shed light on the roles and control of these bacterial communities. Samples of 13 cnidarian species were screened for the presence and diversity of N-acyl-homoserine lactones (AHLs; a prevalent type of QS molecule) using thin-layer chromatography and an Agrobacterium tumefaciens NTL4 biosensor. Ten of 13 were found to harbour species-specific, conserved AHL profiles. AHLs were confirmed in Anemonia viridis using liquid chromatography tandem mass spectrometry. To assess temporal role and stability, AHLs were investigated in A. viridis from intertidal pools over 16 h. Patterns of AHLs showed conserved profiles except for two mid-chain length AHLs, which increased significantly over the day, peaking at 20:00, but had no correlation with pool chemistry. Denaturing gel electrophoresis of RT-PCR-amplified bacterial 16S rRNA showed the presence of an active bacterial community that changed in composition alongside AHL profiles and contained a number of bands that affiliate with known AHL-producing bacteria. Investigations into the quorum sensing-controlled, species-specific roles of these bacterial communities and how these regulatory circuits are influenced by the coral host and members of the bacterial community are imperative to expand our knowledge of these interactions with respect to the maintenance of coral health.

Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.