Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1213351 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR32103971_1.fastq.gz | Fastqsanger.gz | |||
| SRR32103971_2.fastq.gz | Fastqsanger.gz | |||
| SRR32103972_1.fastq.gz | Fastqsanger.gz | |||
| SRR32103972_2.fastq.gz | Fastqsanger.gz | |||
| SRR32103973_1.fastq.gz | Fastqsanger.gz |
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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: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.
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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: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.
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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
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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.
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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: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.
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