Soil metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB11175 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR272362_1.fastq.gz | Fastqsanger.gz | |||
| DRR272362_2.fastq.gz | Fastqsanger.gz | |||
| DRR272363_1.fastq.gz | Fastqsanger.gz | |||
| DRR272363_2.fastq.gz | Fastqsanger.gz | |||
| DRR272364_1.fastq.gz | Fastqsanger.gz |
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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
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Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.
2022-03-01 | PXD009773 | Pride
Project description:The association between soil microbes and plant roots is present in all natural and agricultural environments. Microbes can be beneficial, pathogenic, or neutral to the host plant development and adaptation to abiotic or biotic stresses. Progress in investigating the functions and changes in microbial communities in diverse environments have been rapidly developing in recent years, but the changes in root function is still largely understudied. The aim of this study was to determine how soil bacteria influence maize root transcription and microRNAs (miRNAs) populations in a controlled inoculation of known microbes over a defined time course. At each time point after inoculation of the maize inbred line B73 with ten bacterial isolates, DNA and RNA were isolated from roots. The V4 region of the 16S rRNA gene was amplified from the DNA and sequenced with the Illumina MiSeq platform. Amplicon sequencing of the 16S rRNA gene indicated that most of the microbes successfully colonized maize roots. The colonization was dynamic over time and varied with the specific bacterial isolate. Small RNA sequencing and mRNA-Seq was done to capture changes in the root transcriptome from 0.5 to 480 hours after inoculation. The transcriptome and small RNA analyses revealed epigenetic and transcriptional changes in roots due to the microbial inoculation. This research provides the foundational data needed to understand how plant roots interact with bacterial partners and will be used to develop predictive models for root response to bacteria.
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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
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