Identification and functional characterization of small non-coding RNAs in Xanthomonas oryzae pathovar oryzae

<p>Abstract</p> <p>Background</p> <p>Small non-coding RNAs (sRNAs) are regarded as important regulators in prokaryotes and play essential roles in diverse cellular processes. <it>Xanthomonas oryzae </it>pathovar <it>oryzae </it>(<it>Xoo</it>) is an important plant pathogenic bacterium which causes serious bacterial blight of rice. However, little is known about the number, genomic distribution and biological functions of sRNAs in <it>Xoo</it>.</p> <p>Results</p> <p>Here, we performed a systematic screen to identify sRNAs in the <it>Xoo </it>strain PXO99. A total of 850 putative non-coding RNA sequences originated from intergenic and gene antisense regions were identified by cloning, of which 63 were also identified as sRNA candidates by computational prediction, thus were considered as <it>Xoo </it>sRNA candidates. Northern blot hybridization confirmed the size and expression of 6 sRNA candidates and other 2 cloned small RNA sequences, which were then added to the sRNA candidate list. We further examined the expression profiles of the eight sRNAs in an <it>hfq </it>deletion mutant and found that two of them showed drastically decreased expression levels, and another exhibited an Hfq-dependent transcript processing pattern. Deletion mutants were obtained for seven of the Northern confirmed sRNAs, but none of them exhibited obvious phenotypes. Comparison of the proteomic differences between three of the ΔsRNA mutants and the wild-type strain by two-dimensional gel electrophoresis (2-DE) analysis showed that these sRNAs are involved in multiple physiological and biochemical processes.</p> <p>Conclusions</p> <p>We experimentally verified eight sRNAs in a genome-wide screen and uncovered three Hfq-dependent sRNAs in <it>Xoo</it>. Proteomics analysis revealed <it>Xoo </it>sRNAs may take part in various metabolic processes. Taken together, this work represents the first comprehensive screen and functional analysis of sRNAs in rice pathogenic bacteria and facilitates future studies on sRNA-mediated regulatory networks in this important phytopathogen.</p

A Novel Manganese Efflux System, YebN, Is Required for Virulence by Xanthomonas oryzae pv. oryzae

Manganese ions (Mn2+) play a crucial role in virulence and protection against oxidative stress in bacterial pathogens. Such pathogens appear to have evolved complex mechanisms for regulating Mn2+ uptake and efflux. Despite numerous studies on Mn2+ uptake, however, only one efflux system has been identified to date. Here, we report on a novel Mn2+ export system, YebN, in Xanthomonas oryzae pv. oryzae (Xoo), the causative agent of bacterial leaf blight. Compared with wild-type PXO99, the yebN mutant was highly sensitive to Mn2+ and accumulated high concentrations of intracellular manganese. In addition, we found that expression of yebN was positively regulated by Mn2+ and the Mn2+-dependent transcription regulator, MntR. Interestingly, the yebN mutant was more tolerant to methyl viologen and H2O2 in low Mn2+ medium than PXO99, but more sensitive in high Mn2+ medium, implying that YebN plays an important role in Mn2+ homoeostasis and detoxification of reactive oxygen species (ROS). Notably, deletion of yebN rendered Xoo sensitive to hypo-osmotic shock, suggesting that YebN may protect against such stress. That mutation of yebN substantially reduced the Xoo growth rate and lesion formation in rice implies that YebN could be involved in Xoo fitness in host. Although YebN has two DUF204 domains, it lacks homology to any known metal transporter. Hence, this is the first report of a novel metal export system that plays essential roles in hypo-osmotic and oxidative stress, and virulence. Our results lay the foundations for elucidating the complex and fascinating relationship between metal homeostasis and host-pathogen interactions

SI2-SSI: Collaborative Research: A Software Infrastructure for MPI Performance Engineering: Integrating MVAPICH and TAU via the MPI Tools Interface.

Creating an MPI programming infrastructure that can integrate performance analysis capabilities more directly, through the MPI Tools Information Interface, monitor Performance metrics during run time, and deliver greater optimization opportunities for scientific applications