4 Material und Umwelt
Filtern
Dokumenttyp
- Zeitschriftenartikel (2)
- Buchkapitel (1)
Sprache
- Englisch (3)
Referierte Publikation
- ja (3) (entfernen)
Schlagworte
- Pathogen (3) (entfernen)
Organisationseinheit der BAM
- 4.0 Abteilungsleitung und andere (3) (entfernen)
Rice is staple food of nearly half the world’s population. Rice yields must therefore increase to feed ever larger populations. By colonising rice and other plants, Herbaspirillum spp. stimulate plant growthand productivity. However the molecular factors involved are largely unknown. To further explore this interaction, the transcription profiles of Nipponbare rice roots inoculated with Herbaspirillum seropedicae were determined by RNA-seq. Mapping the 104 million reads against the Oryza sativa cv. Nipponbare genome produced 65 million unique mapped reads that represented 13,840 transcripts each with at least two-times coverage. About 7.4% (1,014) genes were differentially regulated and of these 255 changed expression levels more than two times. Several of the repressed genes encoded proteins related to plant defence (e.g. a putative probenazole inducible protein), plant disease resistance as well as enzymes involved in flavonoid and isoprenoid synthesis. Genes related to the synthesis and efflux of phytosiderophores (PS) and transport of PS-iron complexes were induced by the bacteria. These data suggest that the bacterium represses the rice defence system while concomitantly activating iron uptake. Transcripts of H. seropedicae were also detected amongst which transcripts of genes involved in nitrogen fixation, cell motility and cell wall synthesis were the most expressed.
Emerging infectious diseases arise as a result of novel interactions between populations of hosts and pathogens, and can threaten the health and wellbeing of the entire spectrum of biodiversity. Bees andtheir viruses area case in point. However, detailed knowledge of the ecological factors and evolutionary forces that drive disease emergence in bees and other host–pathogen communities is surprisingly lacking. In this review, we build on the fundamental insight that viruses evolve and adapt over timescales that overlap with host ecology. At the same time, we integrate the role of host community ecology, including community structure and composition, biodiversity loss, and human driven disturbance, all of which represent significant factors in bee virus ecology. Both of these evolutionary and ecological perspectives represent major advances but, in most cases, it remains unclear how evolutionary forces actually operate across different biological scales (e.g., from cell to ecosystem). We present a molecule-to-ecology framework to help address these issues, emphasizing the role of molecular mechanisms as keybottom-up drivers of change at higher ecological scales. We consider the bee–virus system to be an ideal one in which to apply this framework. Unlike many other animal models, bees constitute a well characterized and accessible multispecies assemblage, whose populations and interspecific interactions can be experimentally manipulated and monitored in high resolution across space and time to provide robust tests of prevailing theory.
There are viral, fungal, bacterial and trypanosomal pathogens that negatively impact the individual and superorganismal health of the western honey bee. One fungal pathogen, Ascosphaera apis , affects larvae and causes the disease chalkbrood. A previous genome analysis of As. apis revealed that its genome encodes for RNA interference genes, similar to other fungi and eukaryotes. Here, we examined whether As. apis -targeting double-stranded RNA species could disrupt the germination of As. apis.
We observed that when spores were co-incubated with As. apis -targeting dsRNA, fewer spores were activated for germination, suggesting an uptake of exogenous genetic material at the very onset of germination and consequent damage to essential transcripts needed for germination. Overall, these results indicate that the causative agent of chalkbrood disease, As. apis , can be successfully targeted using an RNAi-based strategy.