Project description:This SuperSeries is composed of the following subset Series: GSE17517: Microarray analysis of high Arctic soil bacterial response to hydrocarbon pollution and bioremediation GSE17532: RT-PCR analysis of high Arctic soil bacterial response to hydrocarbon pollution and bioremediation Refer to individual Series
Project description:These metaproteomic datasets are from active layer soil samples collected from the area of Toolik Field Station, Arctic Alaska, USA. These datasets are described and analyzed in the forthcoming paper, "Functional partitioning and vegetational variation among Arctic soil bacteria revealed by metaproteomics."
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:High Arctic soils have low nutrient availability, low moisture content and very low temperatures and, as such, they pose a particular problem in terms of hydrocarbon bioremediation. An in-depth knowledge of the microbiology involved in this process is likely to be crucial to understand and optimize the factors most influencing bioremediation. Here, we compared two distinct large-scale field bioremediation experiments, located at Alert (ex situ approach) and Eureka (in situ approach), in the Canadian high Arctic. Bacterial community structure and function were assessed using microarrays targeting the 16S rRNA genes of bacteria found in cold environments and hydrocarbon degradation genes as well as reverse-transcriptase real-time PCR targeting key functional genes. Results indicated a large difference between sampling sites in terms of both soil microbiology and decontamination rates. A rapid reorganization of the bacterial community structure and functional potential as well as rapid increases in the expression of alkane monooxygenases and polyaromatic hydrocarbon ring-hydroxylating-dioxygenases were observed one month after the bioremediation treatment commenced in the Alert soils. In contrast, no clear changes in community structure were observed in Eureka soils, while key gene expression increased after a relatively long lag period (1 year). Such discrepancies are likely caused by differences in bioremediation treatments (i.e. ex situ vs. in situ), weathering of the hydrocarbons, indigenous microbial communities, and environmental factors such as soil humidity and temperature. In addition, this study demonstrates the value of molecular tools for the monitoring of polar bacteria and their associated functions during bioremediation. 38 soil samples from two high arctic locations that were contaminated-treated, contaminated or not contaminated followed for up to 4 years
Project description:High Arctic soils have low nutrient availability, low moisture content and very low temperatures and, as such, they pose a particular problem in terms of hydrocarbon bioremediation. An in-depth knowledge of the microbiology involved in this process is likely to be crucial to understand and optimize the factors most influencing bioremediation. Here, we compared two distinct large-scale field bioremediation experiments, located at Alert (ex situ approach) and Eureka (in situ approach), in the Canadian high Arctic. Bacterial community structure and function were assessed using microarrays targeting the 16S rRNA genes of bacteria found in cold environments and hydrocarbon degradation genes as well as reverse-transcriptase real-time PCR targeting key functional genes. Results indicated a large difference between sampling sites in terms of both soil microbiology and decontamination rates. A rapid reorganization of the bacterial community structure and functional potential as well as rapid increases in the expression of alkane monooxygenases and polyaromatic hydrocarbon ring-hydroxylating-dioxygenases were observed one month after the bioremediation treatment commenced in the Alert soils. In contrast, no clear changes in community structure were observed in Eureka soils, while key gene expression increased after a relatively long lag period (1 year). Such discrepancies are likely caused by differences in bioremediation treatments (i.e. ex situ vs. in situ), weathering of the hydrocarbons, indigenous microbial communities, and environmental factors such as soil humidity and temperature. In addition, this study demonstrates the value of molecular tools for the monitoring of polar bacteria and their associated functions during bioremediation. 38 soil samples from two high arctic locations that were contaminated-treated, contaminated or not contaminated followed for up to 4 years
Project description:We investigated the toxicity of soil samples derived from a former municipal landfill site in the South of the Netherlands, where a bioremediation project is running aiming at reusing the site for recreation. Both an organic soil extract and the original soil sample was investigated using the ISO standardised Folsomia soil ecotoxicological testing and gene expression analysis. The 28 day survival/reproduction test revealed that the ecologically more relevant original soil sample was more toxic than the organic soil extract. Microarray analysis showed that the more toxic soil samples induced gene regulatory changes in twice as less genes compared to the soil extract. Consequently gene regulatory changes were highly dependent on sample type, and were to a lesser extent caused by exposure level. An important biological process shared among the two sample types was the detoxification pathway for xenobiotics (biotransformation I, II and III) suggesting a link between compound type and observed adverse effects. Finally, we were able to retrieve a selected group of genes that show highly significant dose-dependent gene expression and thus were tightly linked with adverse effects on reproduction. Expression of four cytochrome P450 genes showed highest correlation values with reproduction, and maybe promising genetic markers for soil quality. However, a more elaborate set of environmental soil samples is needed to validate the correlation between gene expression induction and adverse phenotypic effects.