Project description:Biological soil crusts (BSCs) are cyanobacteria-dominated microbial communities that cover extensive portions of the world’s arid and semi-arid deserts. The infrequent periods of hydration are often too short to allow for dormancy strategies based on sporulation; consequently, survival is based on the unique capabilities of vegetative cells to resuscitate from and re-enter a stress resistant dormant state, one of which is migration within the crust layers in response to hydration. In this study, we sought to characterize the events that govern the emergence of the dominant cyanobacterium from dormancy, its subsequent growth, and the events triggered by re-desiccation and a transition back to dormant state. We performed a 48 hour laboratory wetting experiment of a desert BSC and tracked the response of Microcoleus vaginatus using a whole genome transcriptional time-course including night/day periods. This allowed the identification of genes with a diel expression pattern, genes involved uniquely in the signaling after hydration and those that contribute primarily to desiccation preparation. Desert BSC samples collected from Moab, UT, were hydrated over a period of 48 hours followed by drying induced by removal of water. At periodic times soil samples were harvested and used for RNA extraction and whole genome expression analysis using an expression array representing genes from two strains of M. vaginatus (PCC 9802 and FGP-2)
Project description:Biological soil crusts (BSCs) are cyanobacteria-dominated microbial communities that cover extensive portions of the world’s arid and semi-arid deserts. The infrequent periods of hydration are often too short to allow for dormancy strategies based on sporulation; consequently, survival is based on the unique capabilities of vegetative cells to resuscitate from and re-enter a stress resistant dormant state, one of which is migration within the crust layers in response to hydration. In this study, we sought to characterize the events that govern the emergence of the dominant cyanobacterium from dormancy, its subsequent growth, and the events triggered by re-desiccation and a transition back to dormant state. We performed a 48 hour laboratory wetting experiment of a desert BSC and tracked the response of Microcoleus vaginatus using a whole genome transcriptional time-course including night/day periods. This allowed the identification of genes with a diel expression pattern, genes involved uniquely in the signaling after hydration and those that contribute primarily to desiccation preparation.
Project description:Analysis of microbial community composition in arctic tundra and boreal forest soils using serial analysis of ribosomal sequence tags (SARST). Keywords: other
Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.