Ontology highlight
ABSTRACT:
PROVIDER: PRJNA858415 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Total bacterial DNA was isolated from water and sediment samples from a local watershed and 16S rRNA sequences were analyzed using the Illumina MiSeq v3 platform in order to generate snapshots of bacterial community profiles.
2016-01-01 | GSE73842 | GEO
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.
2023-12-30 | E-MTAB-13326 | biostudies-arrayexpress
Project description:We aimed to investigate the microbial community composition in patients with intracerebral hemorrhage (ICH) and its effect on prognosis. The relationship between changes in bacterial flora and the prognosis of spontaneous cerebral hemorrhage was studied in two cohort studies. Fecal samples from healthy volunteers and patients with intracerebral hemorrhage were subjected to 16S rRNA sequencing at three time points: T1 (within 24 hours of admission), T2 (3 days post-surgery), and T3 (7 days post-surgery) using Illumina high-throughput sequencing technology.
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Project description:Total bacterial DNA was isolated from water and sediment samples from a local watershed and 16S rRNA sequences were analyzed using the Illumina MiSeq v3 platform in order to generate snapshots of bacterial community profiles. A total of 56 samples were collected that represent water and sediment samples from 14 sample sites over two different time points (November 18 and 25, 2011).
2016-07-03 | E-GEOD-73842 | biostudies-arrayexpress
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:Despite the global importance of forests, it is virtually unknown how their soil microbial communities adapt at the phylogenetic and functional level to long term metal pollution. Studying twelve sites located along two distinct gradients of metal pollution in Southern Poland revealed that both community composition (via MiSeq Illumina sequencing of 16S rRNA genes) and functional gene potential (using GeoChip 4.2) were highly similar across the gradients despite drastically diverging metal contamination levels. Metal pollution level significantly impacted microbial community structure (p = 0.037), but not bacterial taxon richness. Metal pollution altered the relative abundance of specific bacterial taxa, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes and Proteobacteria. Also, a group of metal resistance genes showed significant correlations with metal concentrations in soil, although no clear impact of metal pollution levels on overall functional diversity and structure of microbial communities was observed. While screens of phylogenetic marker genes, such as 16S rRNA, provided only limited insight into resilience mechanisms, analysis of specific functional genes, e.g. involved in metal resistance, appeared to be a more promising strategy. This study showed that the effect of metal pollution on soil microbial communities was not straightforward, but could be filtered out from natural variation and habitat factors by multivariate statistical analysis and spatial sampling involving separate pollution gradients.
2014-07-22 | GSE59620 | GEO
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:Sequencing of 16S ribosomal RNA (rRNA) gene, which has improved the characterization of microbial community, has made it possible to detect a low level Helicobacter pylori (HP) sequences even in HP-negative subjects which were determined by a combination of conventional methods. This study was conducted to obtain a cutoff value for HP colonization in gastric mucosa biopsies and gastric juices by the pyrosequencing method. Corresponding author: Department of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam, Gyeonggi-do, Korea; Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea (Tel., +82-31-787-7008; e-mail, nayoungkim49@empas.com). Microbial DNA from gastric mucosal samples [gastric antrum (n=63, mucosal biopsy), follow-up sample on gastric antrum (n=16, mucosal biopsy), and gastric body (n=18, mucosal biopsy)] and gastric juices (n=4, not mucosal biopsy) was amplified by nested PCR using universal bacterial primers, and the 16S rRNA genes were pyrosequenced.
2014-09-18 | E-GEOD-61493 | biostudies-arrayexpress
Project description:Here we report the 16S rRNA sequencing results of human fetal tissues, to identify bacterial genera present in developing fetus.
2021-03-23 | GSE169306 | GEO