Ontology highlight
ABSTRACT:
PROVIDER: PRJNA673669 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12960000_1.fastq.gz | Fastqsanger.gz | |||
| SRR12960000_2.fastq.gz | Fastqsanger.gz | |||
| SRR12960001_1.fastq.gz | Fastqsanger.gz | |||
| SRR12960001_2.fastq.gz | Fastqsanger.gz | |||
| SRR12960002_1.fastq.gz | Fastqsanger.gz |
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Project description:Custom made functional gene micoarray (E-FGA) consisting of 13,056 mRNA-enriched anonymus microbial clones from dirverse microbial communities to profile microbial gene transcript in agricultural soils with low and high flux of N2O. A total of 96 genes displayed expression that differed significantly between low and high N2O emitting soils. Creation and validation of an cDNA microarray from environmental microbial mRNA, to use as a monitoring tool for microbial gene expression
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Project description:Copper has long been applied for agricultural practices. Like other metals, copper is highly persistent in the environment and biologically active long after its use has ceased. Here we present a unique study on the long-term effects (27 years) of copper and pH on soil microbial communities and on Folsomia candida, an important representative of the soil macrofauna, in an experiment with a full factorial, random block design. Bacterial communities were mostly affected by pH. These effects were prominent in Acidobacteria, while Actinobacteria and Gammaroteobacteria communities were affected by original and bioavailable copper. Reproduction and survival of the collembolan F. candida was not affected by the studied copper concentrations. However, the transcriptomic responses to copper reflected a mechanism of copper transport and detoxification, while pH exerted effects on nucleotide and protein metabolism and (acute) inflammatory response. We conclude that microbial community structure explained the history of copper contamination, while gene expression analysis of F. candida is associated with the current level of bioavailable copper. Combined analysis at various trophic levels is highly relevant in the context of assessing long-term soil pollution. A single channel, interwoven loop design was used to test animals exposed to the copper-spiked field soil samples. The field soil was spiked with 4 copper and 4 pH treatments yielding 16 combinations. Combinations are displayed in the Sample descriptions, with 1 M-bM-^@M-^S 4 representing the copper concentrations from low to high, and A-D representing the soil pH from low to high. 4 biological replicates per copper/pH combination were used. Each replicate contained 25 grams of soil and thirty 23-day-old animals.
2012-04-03 | E-GEOD-29644 | biostudies-arrayexpress
Project description:Custom made functional gene micoarray (E-FGA) consisting of 13,056 mRNA-enriched anonymus microbial clones from dirverse microbial communities to profile microbial gene transcript in agricultural soils with low and high flux of N2O. A total of 96 genes displayed expression that differed significantly between low and high N2O emitting soils. Creation and validation of an cDNA microarray from environmental microbial mRNA, to use as a monitoring tool for microbial gene expression Microbial expression profiles comparing two high N2O-emitting sites (3 soil replicates and microarrays each) and two low N2O-emitting sites (3 soil replicates and microarray each) from sugarcane site in Mackay, Australia
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Project description:Herein, we evaluated the changes in biological functions in soils across global biomes through the identification and quantification of proteins. This knowledge is essential to provide one stepforward in soil microbial ecology in order to decipher the cellular and molecular mechanisms employed by soil microbial communities to adapt to their environment and to explain the potential responses of microbial communities, and their microbially-driven ecosystem services, to global change and land use. Our study aims to provide the most comprehensive assessment on the structure and function of the topsoil metaproteome across global biomes, and hence provide direct identification of the most domimant protein-encoded functions in terrestrial ecosystems.
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