Ontology highlight
ABSTRACT:
PROVIDER: PRJNA337891 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR4002120.fastq.gz | Fastqsanger.gz | |||
| SRR4002121.fastq.gz | Fastqsanger.gz | |||
| SRR4002122.fastq.gz | Fastqsanger.gz | |||
| SRR4002123.fastq.gz | Fastqsanger.gz | |||
| SRR4002124.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 13 |
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Project description:16S rRNA amplicon sequencing of New Zealand pasture soils
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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: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: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: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 amplicons from 50 New Zealand pasture soils
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Project description:We report the use of high-throughput sequencing technology to detect the microbial composition and abundance of mice grastic contents before and after Helicobacter pylori infection or Lactobacillus paracasei ZFM54 pretreatment/treatment. The genomic DNA was obtained by the QIAamp PowerFecal DNA Kit. Then, the DNA samples were sent to BGI Genomics Co., Ltd. (Shenzhen, China) for V3-V4 region of the 16S rRNA gene high-throughput sequencing with an Illumina MiSeq platform. DNA samples were sequenced using primers 338F (forward primer sequence ACTCCTACGGGAGGCAGCAG)-806R (reverse primer sequence GGACTACHVGGGTWTCTAAT). The sequencing analyses were carried out using silva138/16s database as a reference for the assignation of Amplicon Sequence Variant (ASV) at 100% similarity.
2022-07-27 | GSE208665 | 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.
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