Soil metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB20184 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Root exudates are composed of primary and secondary metabolites known to modulate the rhizosphere microbiota. Glucosinolates are defense compounds present in the Brassicaceae family capable of deterring pathogens, herbivores and biotic stressors in the phyllosphere. In addition, traces of glucosinolates and their hydrolyzed byproducts have been found in the soil, suggesting that these secondary metabolites could play a role in the modulation and establishment of the rhizosphere microbial community associated with this family. We used Arabidopsis thaliana mutant lines with disruptions in the indole glucosinolate pathway, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 16S rRNA amplicon sequencing to evaluate how disrupting this pathway affects the root exudate profile of Arabidopsis thaliana, and in turn, impacts the rhizosphere microbial community. Chemical analysis of the root exudates from the wild type Columbia (Col-0), a mutant plant line overexpressing the MYB transcription factor ATR1 (atr1D) which increases glucosinolate production, and the loss-of-function cyp79B2cyp79B3 double mutant line with low levels of glucosinolates confirmed that alterations to the indole glucosinolate biosynthetic pathway shifts the root exudate profile of the plant. We observed changes in the relative abundance of exuded metabolites. Moreover, 16S rRNA amplicon sequencing results provided evidence that the rhizobacterial communities associated with the plant lines used were directly impacted in diversity and community composition. This work provides further information on the involvement of secondary metabolites and their role in modulating the rhizobacterial community. Root metabolites dictate the presence of different bacterial species, including plant growth-promoting rhizobacteria. Our results suggest that alterations in the indole glucosinolate pathway cause disruptions beyond the endogenous levels of the plant, significantly changing the abundance and presence of different metabolites in the root exudates of the plants as well as the microbial rhizosphere community.
2023-05-31 | MSV000092068 | MassIVE
Project description:Arsenic (As) bioavailability in the rice rhizosphere is influenced by many microbial interactions, particularly by metal-transforming functional groups at the root-soil interface. This study was conducted to examine As-transforming microbes and As-speciation in the rice rhizosphere compartments, in response to two different water management practices (continuous and intermittently flooded), established on fields with high to low soil-As concentration. Microbial functional gene composition in the rhizosphere and root-plaque compartments were characterized using the GeoChip 4.0 microarray. Arsenic speciation and concentrations were analyzed in the rhizosphere soil, root-plaque, porewater and grain samples. Results indicated that intermittent flooding significantly altered As-speciation in the rhizosphere, and reduced methyl-As and AsIII concentrations in the pore water, root-plaque and rice grain. Ordination and taxonomic analysis of detected gene-probes indicated that root-plaque and rhizosphere assembled significantly different metal-transforming functional groups. Taxonomic non-redundancy was evident, suggesting that As-reduction, -oxidation and -methylation processes were performed by different microbial groups. As-transformation was coupled to different biogeochemical cycling processes establishing functional non-redundancy of rice-rhizosphere microbiome in response to both rhizosphere compartmentalization and experimental treatments. This study confirmed diverse As-biotransformation at root-soil interface and provided novel insights on their responses to water management, which can be applied for mitigating As-bioavailability and accumulation in rice grains.
2021-07-12 | GSE179671 | GEO
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.
2023-05-01 | GSE214656 | GEO
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
2017-05-12 | PXD006118 | Pride
Project description:16S rRNA amplicon sequencing of New Zealand pasture soils
| PRJNA531068 | ENA
Project description:Soil 16s rRNA amplicon (Environmental or incubated)
| PRJDB11175 | ENA
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
2005-11-05 | GSE3525 | GEO