Background: Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date.

The unicellular cyanobacterium Synechocystis sp. PCC 6803 glides toward a light source through the interplay of positive phototaxis genes and proteins. In genetic analysis, the complete disruption of the hybrid sensory kinase sll0043 produced negative phototaxis. Furthermore, Sll0043 was found to be a hub protein by in silico prediction of protein-protein interaction, in which Sll0043 was predominantly linked to seven two-component proteins with high confidence. To understand the regulation and networking of positive phototaxis proteins, the proteomic profile of the sll0043 mutant was compared to that of wild-type. In the sll0043 mutant, 18 spots corresponding to 15 unique proteins were altered by 1.3 to 59 fold; the spots were identified by 2-DE/MALDI-MS analysis. Down-regulated proteins in the sll0043 null-mutant included chaperonins, superoxide dismutase, and phycocyanin beta-subunit. In contrast, nine proteins involved in photosynthesis, translation, regulatory function, and other functions were up-regulated. In particular, a twitching motility protein (PilT1) was induced over 2-fold in sll0043 mutant. Moreover, semi-quantitative and quantitative RT-PCR analysis revealed that pilin (pilA1), pili motor (pilT1), and pili switch gene (pilT2) were significantly increased in sll0043 mutant. These results suggest that the hybrid kinase Sll0043 regulates positive phototaxis by suppressing the expression of pili biosynthesis and regulatory genes and through the interplay with positive phototaxis/motility two-component proteins.

Recently, various IT technologies are utilized to support crop growth management. In farming field, dynamic data analysis while moving is cost efficient tool to farmer. Unlike previous works that not support dynamic analysis, mobile devices need to acquire the most recent data from nearest sensor for efficient processing in mobile device. In this paper, we designed the dynamic crop field analysis methods using mobile sensor node. Using the mobile sensor node, field analysis such as trend, correlation and summary has become more efficient by using dynamic data search and comparing. We implement mobile sensor node and dynamic field analysis application on Win Mobile 6 PDA and evaluated the usefulness in large scale outdoor test-bed of a vineyard in Napa valley.

No abstract

CONSORF is a fully automatic high-accuracy identification system that provides consensus prokaryotic CDS information. It first predicts the CDSs supported by consensus alignments. The alignments are derived from multiple genome-to-proteome comparisons with other prokaryotes using the FASTX program. Then, it fills the empty genomic regions with the CDSs supported by consensus ab initio predictions. From those consensus results, CONSORF provides prediction reliability scores, predicted frame-shifts, alternative start sites and best pair-wise match information against other prokaryotes. These results are easily accessed from a website.