Ontology highlight
ABSTRACT:
PROVIDER: PRJNA480592 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7509370_1.fastq.gz | Fastqsanger.gz | |||
| SRR7509370_2.fastq.gz | Fastqsanger.gz | |||
| SRR7509380_1.fastq.gz | Fastqsanger.gz | |||
| SRR7509380_2.fastq.gz | Fastqsanger.gz | |||
| SRR7509390_1.fastq.gz | Fastqsanger.gz |
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Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
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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. 12 samples were collected from two long-term polluted areas (Olkusz and Miasteczko M-EM-^ZlM-DM-^Eskie) in Southern Poland. In the study presented here, a consecutively operated, well-defined cohort of 50 NSCLC cases, followed up more than five years, was used to acquire expression profiles of a total of 8,644 unique genes, leading to the successful construction of supervised
2014-07-22 | E-GEOD-59620 | biostudies-arrayexpress
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
2016-08-02 | GSE85064 | GEO
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.
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Project description:This study examined how transcriptomics tools can be included in a Triad-based soil quality assessment to assess the toxicity of soils from river banks polluted by metals. To that end we measured chemical soil properties and used the standardized ISO guideline for ecotoxicological tests and a newly developed microarray for gene expression in the indicator soil arthropod, Folsomia candida. Microarray analysis revealed that the oxidative stress response pathway was significantly affected in all soils except one. The data indicate that changes in cell redox homeostasis are a significant signature of metal stress. Finally, 32 genes showed significant dose-dependent expression with metal concentrations. They are promising genetic markers providing an early indication of the need for higher tier testing in soil quality. One of the least polluted soils showed toxicity in the bioassay that could be removed by sterilization. The gene expression profile for this soil did not show a metal-related signature, confirming that another factor than metals (most likely of biological origin) caused the toxicity. This study demonstrates the feasibility and advantages of integrating transcriptomics into Triad-based soil quality assessment. Combining molecular and organismal life-history traitM-bM-^@M-^Ys stress responses helps identifying causes of adverse effect in bioassays. Further validation is needed for verifying the set of genes with dose-dependent expression patterns linked with toxic stress. We used a one-color microarray design where each sample was hybridized to a single array
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