Project description:The toxicity and toxicogenomics of selected anatase and rutile nanoparticles (NP) and bulk titanium dioxide (TiO2) particles were evaluated in the soil nematode Caenorhabditis elegans. Results indicated that bulk or nano-TiO2 particles were slightly toxic to soil nematode C. elegans, as measured by reproduction EC50 values ranging from 4 to 32 mg/L. Whole-genome microarray results indicated that the regulation of glutathione-S-transferase gst-3, cytochrome P450 cypp33-c11, stress resistance regulator scl-1, oxidoreductase wah-1, and embryonic development pod-2 genes were significantly affected by nano-sized and bulk TiO2 particles. More specifically, it was determined that anatase particles exerted a greater effect on metabolic pathways, whereas rutile particles had a greater effect on developmental processes. The up-regulation of the pod-2 gene corroborated the phenotypic effect observed in the reproduction test. Our results demonstrated that C. elegans is a good genomic model for nano-TiO2 toxicity assessment.
2014-07-17 | GSE59470 | GEO
Project description:rhizosphere soil bacterial community under nano-Se
| PRJNA1002267 | ENA
Project description:soil microbial ecology response to Nano particles
Project description:The melting of permafrost and its potential impact on greenhouse gas emissions is a major concern in the context of global warming. The fate of the carbon trapped in permafrost will largely depend on soil physico-chemical characteristics, among which are the quality and quantity of organic matter, pH and water content, and on microbial community composition. In this study, we used microarrays and real-time PCR (qPCR) targeting 16S rRNA genes to characterize the bacterial communities in three different soil types representative of various Arctic settings. The microbiological data were linked to soil physico-chemical characteristics and CO2 production rates. Microarray results indicated that soil characteristics, and especially the soil pH, were important parameters in structuring the bacterial communities at the genera/species levels. Shifts in community structure were also visible at the phyla/class levels, with the soil CO2 production rate being positively correlated to the relative abundance of the Alphaproteobacteria, Bacteroidetes, and Betaproteobacteria. These results indicate that CO2 production in Arctic soils does not only depend on the environmental conditions, but also on the presence of specific groups of bacteria that have the capacity to actively degrade soil carbon.
Project description:Here we have compared adult wildtype (N2) C. elegans gene expression when grown on different bacterial environments/fod sources in an effort to model naturally occuring nematode-bacteria interactions at the Konza Prairie. We hypothesize that human-induced changes to natural environments, such as the addition of nitrogen fertalizer, have effects on the bacterial community in soils and this drives downstream changes in the structure on soil bacterial-feeding nematode community structure. Here we have used transcriptional profiling to identify candidate genes involved in the interaction of nematodes and bacteria in nature.
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.
Project description:RNA microarray was performed to evaluate the efficacy of silicon nano-particles on renal transcriptomes of rats against ischemia reperfusion injury. We compared the transcriptomes of ischemia reperfusion injury model rats with or without oral administration of silicon nano-particles. We also tried to check whether the oral silicon nano-particles intake downregulated the biological processes related to oxidative stress.
Project description:The melting of permafrost and its potential impact on greenhouse gas emissions is a major concern in the context of global warming. The fate of the carbon trapped in permafrost will largely depend on soil physico-chemical characteristics, among which are the quality and quantity of organic matter, pH and water content, and on microbial community composition. In this study, we used microarrays and real-time PCR (qPCR) targeting 16S rRNA genes to characterize the bacterial communities in three different soil types representative of various Arctic settings. The microbiological data were linked to soil physico-chemical characteristics and CO2 production rates. Microarray results indicated that soil characteristics, and especially the soil pH, were important parameters in structuring the bacterial communities at the genera/species levels. Shifts in community structure were also visible at the phyla/class levels, with the soil CO2 production rate being positively correlated to the relative abundance of the Alphaproteobacteria, Bacteroidetes, and Betaproteobacteria. These results indicate that CO2 production in Arctic soils does not only depend on the environmental conditions, but also on the presence of specific groups of bacteria that have the capacity to actively degrade soil carbon. Three different soil types from the Canadian high Arctic were sampled at two depths within the active layer of soil and at two sampling dates (winter and summer conditions), for a total of 20 samples.
Project description:Despite the global importance of forests, it is virtually unknown how their soil microbial communities adapt at the phylogenetic and functional level to long term metal pollution. Studying twelve sites located along two distinct gradients of metal pollution in Southern Poland revealed that both community composition (via MiSeq Illumina sequencing of 16S rRNA genes) and functional gene potential (using GeoChip 4.2) were highly similar across the gradients despite drastically diverging metal contamination levels. Metal pollution level significantly impacted microbial community structure (p = 0.037), but not bacterial taxon richness. Metal pollution altered the relative abundance of specific bacterial taxa, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes and Proteobacteria. Also, a group of metal resistance genes showed significant correlations with metal concentrations in soil, although no clear impact of metal pollution levels on overall functional diversity and structure of microbial communities was observed. While screens of phylogenetic marker genes, such as 16S rRNA, provided only limited insight into resilience mechanisms, analysis of specific functional genes, e.g. involved in metal resistance, appeared to be a more promising strategy. This study showed that the effect of metal pollution on soil microbial communities was not straightforward, but could be filtered out from natural variation and habitat factors by multivariate statistical analysis and spatial sampling involving separate pollution gradients.