Soil Aggregate Bacterial Communities
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ABSTRACT:
PROVIDER: PRJNA644905 | ENA |
REPOSITORIES: ENA
Similar Datasets
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2022-03-01 | PXD009773 | Pride
Project description:To determine whether and how warming affects the functional capacities of the active microbial communities, GeoChip 5.0 microarray was used. Briefly, four fractions of each 13C-straw sample were selected and regarded as representative for the active bacterial community if 16S rRNA genes of the corresponding 12C-straw samples at the same density fraction were close to zero.
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Project description:Iron-rich pelagic aggregates (iron snow) were collected directly onto silicate glass filters using an electronic water pump installed below the redoxcline. RNA was extracted and library preparation was done using the NEBNext Ultra II directional RNA library prep kit for Illumina. Data was demultiplied by GATC sequencing company and adaptor was trimmed by Trimgalore. After trimming, data was processed quality control by sickle and mRNA/rRNA sequences were sorted by SortmeRNA. mRNA sequences were blast against NCBI-non redundant protein database and the outputs were meganized in MEGAN to do functional analysis. rRNA sequences were further sorted against bacterial/archeal 16S rRNA, eukaryotic 18S rRNA and 10,000 rRNA sequences of bacterial 16S rRNA, eukaryotic 18S rRNA were subset to do taxonomy analysis.
2021-10-15 | E-MTAB-9686 | biostudies-arrayexpress
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:16S rRNA amplicon sequences from a 5th order mountain stream network, Oregon, USA
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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.
2017-05-12 | PXD006118 | Pride
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:We characterized the bacterial diversity of chlorinated drinking water from three surface water treatment plants supplying the city of Paris, France. For this purpose, we used serial analysis of V6 ribosomal sequence tag (SARST-V6) to produce concatemers of PCR-amplified ribosomal sequence tags (RSTs) from the V6 hypervariable region of the 16S rRNA gene for sequence analysis. Using SARST-V6, we obtained bacterial profiles for each drinking water sample, demonstrating a strikingly high degree of biodiversity dominated by a large collection of low-abundance phylotypes. In all water samples, between 57.2-77.4% of the sequences obtained indicated bacteria belonging to the Proteobacteria phylum. Full-length 16S rDNA sequences were also generated for each sample, and comparison of the RSTs with these sequences confirmed the accurate assignment for several abundant bacterial phyla identified by SARST-V6 analysis, including members of unclassified bacteria, which account for 6.3-36.5% of all V6 sequences. These results suggest that these bacteria may correspond to a common group adapted to drinking water systems. The V6 primers used were subsequently evaluated with a computer algorithm to assess their hybridization efficiency. Potential errors associated with primer-template mismatches and their impacts on taxonomic group detection were investigated. The biodiversity present in all three drinking water samples suggests that the bacterial load of the drinking water leaving treatment plants may play an important role in determining the downstream community dynamics of water distribution networks. 3 different drinking water samples (Orly, Ivry, Joinville drinking water sample)
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