Soil metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB13031 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR346241_1.fastq.gz | Fastqsanger.gz | |||
| DRR346241_2.fastq.gz | Fastqsanger.gz | |||
| DRR346242_1.fastq.gz | Fastqsanger.gz | |||
| DRR346242_2.fastq.gz | Fastqsanger.gz | |||
| DRR346243_1.fastq.gz | Fastqsanger.gz |
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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 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).
2025-05-28 | GSE282587 | GEO
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).
2025-05-28 | GSE282586 | GEO
Project description:16S rRNA amplicon sequencing of New Zealand pasture soils
| PRJNA531068 | ENA
Project description:Because of severe abiotic limitations, Antarctic soils represent simplified ecosystems, where microorganisms are the principle drivers of nutrient cycling. This relative simplicity makes these ecosystems particularly vulnerable to perturbations, like global warming, and the Antarctic Peninsula is among the most rapidly warming regions on the planet. However, the consequences of the ongoing warming of Antarctica on microorganisms and the processes they mediate are unknown. Here, using 16S rRNA gene pyrosequencing and qPCR, we report a number of highly consistent changes in microbial community structure and abundance across very disparate sub-Antarctic and Antarctic environments following three years of experimental field warming (+ 0.5-2°C). Specifically, we found significant increases in the abundance of fungi and bacteria and in the Alphaproteobacteria-to-Acidobacteria ratio. These alterations were linked to a significant increase in soil respiration. Furthermore, the shifts toward generalist or opportunistic bacterial communities following warming weakened the linkage between bacterial diversity and functional diversity. Warming also increased the abundance of some organisms related to the N-cycle, detected as an increase in the relative abundance of nitrogenase genes via GeoChip microarray analyses. Our results demonstrate that soil microorganisms across a range of sub-Antarctic and Antarctic environments can respond consistently and rapidly to increasing temperatures, thereby potentially disrupting soil functioning. We conducted in situ warming experiments for three years using open-top chambers (OTCs) at one sub-Antarctic (Falkland Islands, 52ºS) and two Antarctic locations (Signy and Anchorage Islands, 60ºS and 67ºS respectively) (see Supplementary Fig. 1 for a map). OTCs increased annual soil temperature by an average of 0.8°C (at a depth of 5 cm), resulting in 8-43% increase in positive-degree days annually and a decrease in freeze-thaw cycle frequency by an average of 15 cycles per year (8). At each location, we included densely vegetated and bare fell-field soils in the experimental design for a total of six environments. Densely vegetated and bare environments represent two contrasting environments for Antarctic soil microorganisms, with large differences in terms of C and N inputs to soils. Massively parallel pyrosequencing (Roche 454 GS FLX Titanium) of 16S rRNA gene amplicons was used to follow bacterial diversity and community composition [GenBank Accession Numbers: HM641909-HM744649], and functional gene microarrays (GeoChip 2.0)(11) were used to assess changes in functional gene distribution. Bacterial and fungal communities were also quantified using real-time PCR.
2010-12-30 | E-GEOD-22825 | biostudies-arrayexpress
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
2025-06-15 | GSE298403 | GEO
Project description:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
| 2255499 | ecrin-mdr-crc
Project description:Cover cropping is an effective method to protect agricultural soils from erosion, promote nutrient and moisture retention, encourage beneficial microbial activity, and maintain soil structure. Reusing winter cover crop root channels with the maize roots during the summer allows the cash crop to extract resources from farther niches in the soil horizon. In this study, we investigate how reusing winter cover crop root channels to grow maize (Zea mays L.) affects the composition and function of the bacterial communities in the rhizosphere using 16S rRNA gene amplicon sequencing and metaproteomics. We discovered that the bacterial community significantly differed among cover crop variations, soil profile depths, and maize growth stages. Re-usage of the root channels increased bacterial abundance, and it further increases as we elevate the complexity from monocultures to mixtures. Upon mixing legumes with brassicas and grasses, the overall expression of several steps of the carbon cycle (C) and the nitrogen cycle (N) improved. The deeper root channels of legumes and brassicas compared to grasses correlated with higher bacterial 16S rRNA gene copy numbers and community roles in the respective variations in the subsoil regimes due to the increased availability of root exudates secreted by maize roots. In conclusion, root channel re-use (monocultures and mixtures) improved the expression of metabolic pathways of the important C and N cycles, and the bacterial communities, which is beneficial to the soil rhizosphere as well as to the growing crops.
2025-05-02 | PXD046832 | Pride
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: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