Ontology highlight
ABSTRACT:
PROVIDER: PRJNA956846 | ENA |
REPOSITORIES: ENA
Similar Datasets
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: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:To effectively monitor microbial populations in acidic environments and bioleaching systems, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the known genes associated with the acidophiles. This array contained 1,072 probes in which there were 571 related to 16S rRNA and 501 related to functional genes. Acid mine drainage (AMD) presents numerous problems to the aquatic life and surrounding ecosystems. However, little is known about the geographic distribution, diversity, composition, structure and function of AMD microbial communities. In this study, we analyzed the geographic distribution of AMD microbial communities from twenty sites using restriction fragment length polymorphism (RFLP) analysis of 16S rRNA genes, and the results showed that AMD microbial communities were geographically distributed and had high variations among different sites. Then an AMD-specific microarray was used to further analyze nine AMD microbial communities, and showed that those nine AMD microbial communities had high variations measured by the number of detected genes, overlapping genes between samples, unique genes, and diversity indices. Statistical analyses indicated that the concentrations of Fe, S, Ca, Mg, Zn, Cu and pH had strong impacts on both phylogenetic and functional diversity, composition, and structure of AMD microbial communities. This study provides insights into our understanding of the geographic distribution, diversity, composition, structure and functional potential of AMD microbial communities and key environmental factors shaping them. This study investigated the geographic distribution of Acid Mine Drainages microbial communities using a 16S rRNA gene-based RFLP method and the diversity, composition and structure of AMD microbial communities phylogenetically and functionally using an AMD-specific microarray which contained 1,072 probes ( 571 related to 16S rRNA and 501 related to functional genes). The functional genes in the microarray were involved in carbon metabolism (158), nitrogen metabolism (72), sulfur metabolism (39), iron metabolism (68), DNA replication and repair (97), metal-resistance (27), membrane-relate gene (16), transposon (13) and IST sequence (11).
2011-03-08 | E-GEOD-27542 | biostudies-arrayexpress
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. 12 samples were collected from two long-term polluted areas (Olkusz and Miasteczko M-EM-^ZlM-DM-^Eskie) in Southern Poland. In the study presented here, a consecutively operated, well-defined cohort of 50 NSCLC cases, followed up more than five years, was used to acquire expression profiles of a total of 8,644 unique genes, leading to the successful construction of supervised
2014-07-22 | E-GEOD-59620 | biostudies-arrayexpress
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: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
Project description:A combination of shotgun metaproteomics and 16S rRNA gene pyrosequencing wasused to identify potential functional pathways and key microorganisms involved in long-chain fatty acids (LCFA) anaerobic conversion. Microbial communities degrading saturated- and unsaturated-LCFA were compared. Archaeal communities were mainly composed of Methanosaeta, Methanobacterium and Methanospirillum species, both in stearate (saturated C18:0) and oleate (mono-unsaturated C18:1) incubations. Over 80% of the 16S rRNA gene sequences clustered within the Methanosaeta genus, which is in agreement with the high number of proteins assigned to this group (94%). Archaeal proteins related with methane metabolism were highly expressed. Bacterial communities were rather diverse and the composition dissimilar between incubations with saturated- and unsaturated-LCFA. Stearate-degrading communities were enriched in Deltaproteobacteria (34% of the assigned sequences), while microorganisms clustering within the Synergistia class were more predominant in oleate incubation (25% of the assigned sequences). Bacterial communities were diverse and active, given by the high percentage of proteins related with mechanisms of energy production. Several proteins were assigned to syntrophic bacteria, emphasizing the importance of the interactions between acetogens and methanogens in energy exchange and formation in anaerobic LCFA-rich environments.
2024-05-03 | PXD047824 | Pride
Project description:A combination of shotgun metaproteomics and 16S rRNA gene pyrosequencing wasused to identify potential functional pathways and key microorganisms involved in long-chain fatty acids (LCFA) anaerobic conversion. Microbial communities degrading saturated- and unsaturated-LCFA were compared. Archaeal communities were mainly composed of Methanosaeta, Methanobacterium and Methanospirillum species, both in stearate (saturated C18:0) and oleate (mono-unsaturated C18:1) incubations. Over 80% of the 16S rRNA gene sequences clustered within the Methanosaeta genus, which is in agreement with the high number of proteins assigned to this group (94%). Archaeal proteins related with methane metabolism were highly expressed. Bacterial communities were rather diverse and the composition dissimilar between incubations with saturated- and unsaturated-LCFA. Stearate-degrading communities were enriched in Deltaproteobacteria (34% of the assigned sequences), while microorganisms clustering within the Synergistia class were more predominant in oleate incubation (25% of the assigned sequences). Bacterial communities were diverse and active, given by the high percentage of proteins related with mechanisms of energy production. Several proteins were assigned to syntrophic bacteria, emphasizing the importance of the interactions between acetogens and methanogens in energy exchange and formation in anaerobic LCFA-rich environments.
2024-05-03 | PXD047617 | Pride