Project description:Comparison of probe-target dissociations of probe Eub338 and Gam42a with native RNA of P. putida, in vitro transcribed 16s rRNA of P. putida, in vitro transcribed 16S rRNA of a 2,4,6-trinitrotoluene contaminated soil and an uncontaminated soil sample. Functional ANOVA revealed no significant differences in the dissociation curves of probe Eub338 when hybridised to the different samples. On the opposite, the dissociation curve of probe Gam42a with native RNA of P. putida was significantly different than the dissociation curves obtained with in vitro transcribed 16S rRNA samples. Keywords: Microbial diversity, thermal dissociation analysis, CodeLink microarray
Project description:Investigation of the phylogenetic diversity of Acidobacteria taxa using PCR amplicons from positive control 16S rRNA templates and total genomic DNA extracted from soil and a soil clay fraction A ten chip study using PCR amplicons from cloned 16S rRNA genes and from diverse soil 16S rRNAs, with PCR primers specific to the Division Acidobacteria. Each chip measures the signal from 42,194 probes (in triplicate) targeting Acidobacteria division, subdivision, and subclades as well as other bacterial phyla. All samples except one (GSM464591) include 2.5 M betaine in the hybridization buffer. Pair files lost due to a computer crash.
Project description:Investigation of the phylogenetic diversity of Acidobacteria taxa using PCR amplicons from positive control 16S rRNA templates and total genomic DNA extracted from soil and a soil clay fraction
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.
Project description:Microbial community analysis with DNA oligonucleotide microarrays targeting ribosomal RNA (rRNA) provides a highly parallel interrogation of nucleic acids isolated from environmental samples. High fidelity readout is essential for accurate interpretation of hybridisations. We describe the hybridisation of in vitro transcribed 16S rRNA from an uncontaminated and 2,4,6-trinitrotoluene contaminated soil to an oligonucleotide microarray containing group- and species-specific perfect match (PM) probes and their 2 corresponding mismatch (MM) probes. Thermal dissociation analysis was used to determine the specificity of each PM-MM probe set. Functional ANOVA often discriminated PM-MM probe sets when Td values (temperature at 50% probe-target dissociation) could not. Maximum discrimination for many PM and MM probes often occurred at temperatures greater than the Td. Comparison of signal intensities measured prior to dissociation analysis from hybridisations of the two soil samples revealed significant differences in domain-, group- and species-specific probes. Functional ANOVA showed significantly different dissociation curves for 11 PM probes when hybridisations from the two soil samples were compared, even though initial signal intensities for 3 of the 11 did not vary. This approach provides a highly parallel, multi-level analysis that incorporates MM probes and dissociation curves into high fidelity microarray analysis of complex environmental nucleic acid profiles. Keywords: Microbial diversity, thermal dissociation analysis
Project description:Gut microbial profiling of uterine fibroids (UFs) patients comparing control subjects. The gut microbiota was examined by 16S rRNA quantitative arrays and bioinformatics analysis. The goal was to reveal alterations in the gut microbiome of uterine fibroids patients.
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. Three different soil types from the Canadian high Arctic were sampled at two depths within the active layer of soil and at two sampling dates (winter and summer conditions), for a total of 20 samples.
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:Bioinformatics pipelines comparison for the analyses of 16S metagenomic data in clinical samples