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:For further validation that the circulating tumor cells (CTCs) from head and neck squamous cell carcinomas (HNSCC) patients were indeed cancer cells rather than non-specific contaminated cells such as white blood cells (WBCs), we examined the copy number alterations (CNAs) of the captured CTCs by aCGH (array comparative genomic hybridization).
Project description:This SuperSeries is composed of the following subset Series: GSE28606: Monitoring of functional gene responses to ERD (enhanced reductive dechlorination) from four TCE-contaminated sites GSE28608: Monitoring of functional gene responses to biostimulation from a TCE-contaminated site Refer to individual Series
Project description:Geobacteraceae transfer electrons from a donor such as acetate to an electron acceptor such as Fe(III) or U(VI). Geobacter uraniireducens is found in uranium-contaminated sites and plays an important role in in situ bioremediation. In this experiment, gene expression was compared between G. uraniireducens cultures grown in sediments from a uranium contaminated site amended with acetate and cultures grown in acetate/fumarate medium. Keywords: two-condition comparison
2008-10-20 | GSE10920 | GEO
Project description:Metagenomics analysis of arsenic contaminated samples
Project description:A functional microarray targeting 24 genes involved in chlorinated solvent biodegradation pathways has been developed and used to monitor the gene diversity present in four trichloroethylene (TCE) contaminated sites under ERD (enhanced reductive dechlorination) treatment. The microarray format provided by NimbleGen and used in this study is 12x135K. 2 µg of labelled gDNA from 30 groundwater samples were hybridized on the microarrays.
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.