Genomotyping of Pseudomonas putida strains using P-putida KT2440-based high-density DNA microarrays: implications for transcriptomics studies

Pseudomonas putida KT2440 is the only fully sequenced P. putida strain. Thus, for transcriptomics and proteomics studies with other P. putida strains, the P. putida KT2440 genomic database serves as standard reference. The utility of KT2440 whole-genome, high-density oligonucleotide microarrays for transcriptomics studies of other Pseudomonas strains was investigated. To this end, microarray hybridizations were performed with genomic DNAs of subcultures of P. putida KT2440 (DSM6125), the type strain (DSM291(T)), plasmid pWW0-containing KT2440-derivative strain mt-2 (DSM3931), the solvent-tolerant P. putida S12, and several other Pseudomonas strains. Depending on the strain tested, 22 to 99% of all genetic elements were identified in the genomic DNAs. The efficacy of these microarrays to study cellular function was determined for all strains included in the study. The vast majority of DSM6125 genes encoding proteins of primary metabolism and genes involved in the catabolism of aromatic compounds were identified in the genomic DNA of strain S12: a prerequisite for reliable transcriptomics analyses. The genomotypic comparisons between Pseudomonas strains were used to construct highly discriminative phylogenetic relationships. DSM6125 and DSM3931 were indistinguishable and clustered together with strain S12 in a separate group, distinct from DSM291(T). Pseudomonas monteilii (DSM14164) clustered well with P. putida strains.

Catalytic role of gold in gold-based catalysts: A density functional theory study on the CO oxidation on gold

Gold-based catalysts have been of intense interests in recent years, being regarded as a new generation of catalysts due to their unusually high catalytic performance. For example, CO oxidation on Au/TiO2 has been found to occur at a temperature as low as 200 K. Despite extensive studies in the field, the microscopic mechanism of CO oxidation on Au-based catalysts remains controversial. Aiming to provide insight into the catalytic roles of Au, we have performed extensive density functional theory calculations for the elementary steps in CO oxidation on Au surfaces. O atom adsorption, CO adsorption, O-2 dissociation, and CO oxidation on a series of Au surfaces, including flat surfaces, defects and small clusters, have been investigated in detail. Many transition states involved are located, and the lowest energy pathways are determined. We find the following: (i) the most stable site for O atom on Au is the bridge site of step edge, not a kink site; (ii) O-2 dissociation on Au (O-2-->20(ad)) is hindered by high barriers with the lowest barrier being 0.93 eV on a step edge; (iii) CO can react with atomic O with a substantially lower barrier, 0.25 eV, on Au steps where CO can adsorb; (iv) CO can react with molecular O-2 on Au steps with a low barrier of 0.46 eV, which features an unsymmetrical four-center intermediate state (O-O-CO); and (v) O-2 can adsorb on the interface of Au/TiO2 with a reasonable chemisorption energy. On the basis of our calculations, we suggest that (i) O-2 dissociation on Au surfaces including particles cannot occur at low temperatures; (ii) CO oxidation on Au/inactive-materials occurs on Au steps via a two-step mechanism: CO+O-2-->CO2+O, and CO+O-->CO2; and (iii) CO oxidation on Au/active-materials also follows the two-step mechanism with reactions occurring at the interface.

Image segmentation based on multi-scan constraint satisfaction neural network

A novel image segmentation method based on a constraint satisfaction neural network (CSNN) is presented. The new method uses CSNN-based relaxation but with a modified scanning scheme of the image. The pixels are visited with more distant intervals and wider neighborhoods in the first level of the algorithm. The intervals between pixels and their neighborhoods are reduced in the following stages of the algorithm. This method contributes to the formation of more regular segments rapidly and consistently. A cluster validity index to determine the number of segments is also added to complete the proposed method into a fully automatic unsupervised segmentation scheme. The results are compared quantitatively by means of a novel segmentation evaluation criterion. The results are promising.