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: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: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: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:To determine whether and how warming affects the functional capacities of the active microbial communities, GeoChip 5.0 microarray was used. Briefly, four fractions of each 13C-straw sample were selected and regarded as representative for the active bacterial community if 16S rRNA genes of the corresponding 12C-straw samples at the same density fraction were close to zero.
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:The goal of this growth chamber experiment was to investigate the effects of diverse soil microbial communities on the transcriptional responses of plants to drought. Specifically, we sought to understand how soil microbiomes' past exposure to water-limited conditions (either long-term exposure to dry conditions in low-precipitation sites, or recent acute drought) impacted their interactions with plants. Six soils collected from remnant prairies crossing a steep precipitation gradient in Kansas, USA were used as the starting microbial communities. Thirty-two pots (or mesocosms) of each soil were divided among four treatments: droughted or well-watered, and with or without a host plant (Tripsacum dactyloides) in a factorial design. The soil mesocosms were "conditioned" in these treatments for five months. (Metagenome and metatranscriptome data from the baseline soils and the post-conditioning soils are available in a separate BioProject on NCBI SRA and GEO). Then, a microbial slurry extracted from each of the 192 conditioned soils was used to inoculate 4 plants in a subsequent experiment (the “Test Phase”): one pot per combination of watering treatment (droughted or control) and host species (Zea mays or Tripsacum dactyloides). After 4 weeks (for maize) or 5 weeks (for eastern gamagrass) we harvested one crown root per plant for 16S rRNA sequencing and another crown root for RNA-seq. The 16S and RNA-seq data for these plants (both species) are contained in this BioProject. Note that 16S rRNA sequencing data are available for all plants in this experiment, but we conducted RNA-seq only for a subset (all plants grown in microbiomes originating from the 2 driest and 2 wettest collection sites).