Project description:Plants and rhizosphere microbes rely closely on each other, with plants supplying carbon to bacteria in root exudates, and bacteria mobilizing soil-bound phosphate for plant nutrition. When the phosphate supply becomes limiting for plant growth, the composition of root exudation changes, affecting rhizosphere microbial communities and microbially-mediated nutrient fluxes. To evaluate how plant phosphate deprivation affects rhizosphere bacteria, Lolium perenne seedlings were root-inoculated with Pseudomonas aeruginosa 7NR, and grown in axenic microcosms under different phosphate regimes (330 uM vs 3-6 uM phosphate). The effect of biological nutrient limitation was examined by DNA microarray studies of rhizobacterial gene expression.
Project description:This experiment aimed to understand stress responses of microbial communities differing in chronic exposure to the photosynthesis inhibitor diuron, combining untargeted metatranscriptomics (RNA-seq) and dose-response design. First, river microbial communities were incubated for 5-weeks in microcosms 1/ under constant exposure to 4µg/L of diuron (stressed community) or 2/ without contamination (non-stressed community). Then, both communities were exposed for 1 hour to a gradient of diuron concentrations to investigate differences in stress responses after chronic exposure. This experimental design enabled the determination of contig response trends as well as sensitivity thresholds.
Project description:To unravel complex dynamics of environmental disturbance and microbial metabolic activities, we set up laboratory microcosms to investigate the effects of SO42- and O2 alone or in combination on microbial activities and interactions, as well as the resulting fate of carbon within wetland soil. We used proteogenomics to characterize the biochemical and physiological responses of microbial communities to individual perturbations and their combined effects. Stoichiometric models were employed to deconvolute carbon exchanges among the main functional guilds. These findings can contribute to the development of mechanistic models for predicting greenhouse gas emissions from wetland ecosystems under various climate change scenarios.