The pneumococcal genome is variable and there are minimal data on the influence of the accessory genome on phenotype. Pneumococcal serotype 14 sequence type (ST) 46 had been the most prevalent clone causing pneumonia in children in Taiwan. A microarray was constructed using the genomic DNA of a clinical strain (NTUH-P15) of serotype 14 ST46. Using DNA hybridization, genomic variations in NTUH-P15 were compared to those of 3 control strains. Microarray analysis identified 7 genomic regions that had significant increases in hybridization signals in the NTUH-P15 strain compared to control strains. One of these regions encoded PblB, a phage-encoded virulence factor implicated (in Streptococcus mitis) in infective endocarditis. The isogenic pblB mutant decreased adherence to A549 human lung epithelial cell compared to wild-type NTUH-P15 strain (P = 0.01). Complementation with pblB restored the adherence. PblB is predicted to contain a galactose-binding domain-like region. Preincubation of NTUH-P15 with D-galactose resulted in decreases of adherence to A549 cell in a dose-dependent manner. Challenge of mice with NTUH-P15, isogenic pblB mutant and pblB complementation strains determined that PblB was required for bacterial persistence in the nasopharynx and lung. PblB, as an adhesin mediating the galactose-specific adhesion activity of pneumococci, promote pneumococcal clonal success.
Wireless sensor nodes are usually densely deployed to completely cover (monitor) a set of targets. Consequently, redundant sensor nodes that are not currently needed in the covering task can be powered off to conserve energy. These sensors can take over the covering task later to prolong network lifetime. The coverage problem, concerns picking up a set of working sensors that collectively meet the coverage requirements. The problem is complicated by the possibility that targets may have different coverage requirements while sensor nodes may have different amounts of energy. This article proposes a game-theoretic approach to the coverage problem, where each sensor autonomously decides its state with a simple rule based on local information. We give rigorous proofs to show stability, correctness, and efficiency of the proposed game. Implementation variants of the game consider specific issues, such as game convergence time and different amounts of sensor energy. Simulation results show significant improvement in network lifetime by the proposed approach when compared with representative alternatives.
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