UK SOILS
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR059346.fastq.gz | Fastqsanger.gz | |||
| ERR059347.fastq.gz | Fastqsanger.gz | |||
| ERR059348.fastq.gz | Fastqsanger.gz | |||
| ERR059349.fastq.gz | Fastqsanger.gz | |||
| ERR059350.fastq.gz | Fastqsanger.gz |
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Project description:Understanding biological diversity and distribution patterns at multiple spatial scales is a central issue in ecology. Here, we investigated the biogeographical patterns of functional genes in soil microbes from 24 arctic heath sites using GeoChip-based metagenomics and principal coordinates of neighbour matrices (PCNM)-based analysis. Functional gene richness varied considerably among sites, while the proportions of each major functional gene category were evenly distributed. Functional gene composition varied significantly at most medium and broad spatial scales, and the PCNM analyses indicated that 14-20% of the variation in total and major functional gene categories could be attributed primarily to relatively broad-scale spatial effects that were consistent with broad-scale variation in soil pH and total nitrogen. The combination of variance partitioning and multi-scales analysis indicated that spatial distance effects contributed 12% to variation in functional gene composition，whereas environmental factors contributed only 3%. This relatively strong influence of spatial as compared to environmental variation in determining functional gene distributions contrasts sharply with typical microbial phylotype/species-based biogeographical patterns in the Arctic and elsewhere. Our results suggest that the distributions of soil functional genes cannot be predicted from phylogenetic distributions because spatial factors associated with historical contingencies are relatively important determinants of their biogeography.
2014-12-10 | GSE63927 | 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.
2014-07-22 | GSE59620 | GEO
Project description:In this work, we used a functional gene microarray approach (GeoChip) to assess the soil microbial community functional potential related to the different wine quality. In order to minimize the soil variability, this work was conducted at a “within-vineyard” scale, comparing two similar soils (BRO11 and BRO12) previously identified with respect to pedological and hydrological properties within a single vineyard in Central Tuscany and that yielded highly contrasting wine quality upon cultivation of the same Sangiovese cultivar
2020-03-04 | GSE146289 | GEO
Project description:Understanding the environmental factors that shape microbial communities is crucial, especially in extreme environments, like Antarctica. Two main forces were reported to influence Antarctic soil microbes: birds and plants. Both birds and plants are currently undergoing unprecedented changes in their distribution and abundance due to global warming. However, we need to clearly understand the relationship between plants, birds and soil microorganisms. We therefore collected rhizosphere and bulk soils from six different sampling sites subjected to different levels of bird influence and colonized by Colobanthus quitensis and Deschampsia antarctica in the Admiralty Bay, King George Island, Maritime Antarctic. Microarray and qPCR assays targeting 16S rRNA genes of specific taxa were used to assess microbial community structure, composition and abundance and analyzed with a range of soil physico-chemical parameters. The results indicated significant rhizosphere effects in four out of the six sites, including areas with different levels of bird influence. Acidobacteria were significantly more abundant in soils with little bird influence (low nitrogen) and in bulk soil. In contrast, Actinobacteria were significantly more abundant in the rhizosphere of both plant species. At two of the sampling sites under strong bird influence (penguin colonies), Firmicutes were significantly more abundant in D. antarctica rhizosphere but not in C. quitensis rhizosphere. The Firmicutes were also positively and significantly correlated to the nitrogen concentrations in the soil. We conclude that the microbial communities in Antarctic soils are driven both by bird and plants, and that the effect is taxa-specific.
2012-06-01 | GSE33847 | GEO
Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities
2009-06-01 | GSE13977 | 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. 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:The availability of organic carbon represents a major bottleneck for the development of soil microbial communities and the regulation of microbially-mediated ecosystem processes. However, there is still a lack of knowledge on how the lifestyle and population abundances are physiologically regulated by the availability of energy and organic carbon in soil ecosystems. To date, functional insights into the lifestyles of microbial populations have been limited by the lack of straightforward approaches to the tracking of the active microbial populations. Here, by the use of an comprehensiv metaproteomics and genomics, we reveal that C-availability modulates the lifestyles of bacterial and fungal populations in drylands and determines the compartmentalization of functional niches. This study highlights that the active diversity (evaluated by metaproteomics) but not the diversity of the whole microbial community (estimated by genome profiling) is modulated by the availability of carbon and is connected to the ecosystem functionality in drylands.
2017-07-07 | PXD003572 | Pride
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.
2011-01-01 | GSE24800 | GEO
Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities We used lignin degradation as a model process to demonstrate the use of an oligonucleotide microarray for directly detecting gene expression in soil communities using signal amplification instead of template amplification to avoid the introduction of PCR bias. In the current study, we analyzed mRNA isolated from two distinct soil microbial communities and demonstrate our ability to detect the expression of a small subset of lignin degrading genes following exposure to a lignitic substrate. We also included purified control amplicons and mixed target experiments with pure P. chrysosporium genomic cDNA to determine the level of interference from soil biomass on target hybridization.
2010-05-18 | E-GEOD-13977 | biostudies-arrayexpress
Project description:Microbial communities in the rhizosphere make significant contributions to crop health and nutrient cycling. However, their ability to perform important biogeochemical processes remains uncharacterized. Important functional genes, which characterize the rhizosphere microbial community, were identified to understand metabolic capabilities in the maize rhizosphere using GeoChip 3.0-based functional gene array method. Triplicate samples were taken for both rhizosphere and bulk soil, in which each individual sample was a pool of four plants or soil cores. To determine the abundance of functional genes in the rhizosphere and bulk soils, GeoChip 3.0 was used.
2014-09-12 | E-GEOD-61338 | biostudies-arrayexpress