Ontology highlight
ABSTRACT:
PROVIDER: PRJNA752974 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15371500.fastq.gz | Fastqsanger.gz | |||
| SRR15371500_1.fastq.gz | Fastqsanger.gz | |||
| SRR15371500_2.fastq.gz | Fastqsanger.gz | |||
| SRR15371501.fastq.gz | Fastqsanger.gz | |||
| SRR15371501_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 159 |
Similar Datasets
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.
2024-04-14 | E-MTAB-13075 | 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.
2014-07-22 | GSE59620 | GEO
Project description:The model prokaryote Escherichia coli can exist as a either a commensal or a pathogen in the gut of diverse mammalian hosts. These associations, coupled with its ease of cultivation and genetic variability, have made E. coli a popular indicator organism for tracking the origin of fecal water contamination. Source tracking accuracy is predicated on the assumption that E. coli isolates recovered from contaminated water present a genetic signature characteristic of the host from which they originated. In this study, we compared the accuracy with which E. coli isolated from humans, bear, cattle and deer could be identified by standard fingerprinting methods used for library-based microbial source tracking (repetitive element PCR and pulsed-field gel electrophoresis) in relation to microarray-based analysis of genome content. Our results show that patterns of gene presence or absence were more useful for distinguishing E. coli isolates from different sources than traditional fingerprinting methods, particularly in the case of human strains. Host-associated differences in genome composition included the presence or absence of mobile IS1 elements as well as genes encoding the ferric dicitrate iron transporter (fec), E. coli common pilus (ECP), type 1 fimbriae and the CRISPR associated cas proteins. Many of these differences occurred in regions of the E. coli chromosome previously shown to be “hot spots” for the integration of horizontally-acquired DNA. PCR primers designed to amplify the IS1 and fec loci confirmed array results and demonstrated the ease with which gene presence/absence data can be converted into a diagnostic assay. The data presented here suggest that, despite the high level of genetic diversity observed among isolates by PFGE, human-derived strains may constitute a distinct ecotype distinguished by multiple potential library-independent source tracking markers.
2013-03-01 | GSE21115 | GEO
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:To assess the impact of surface water across the Hun River, several sampling sites located in the mainstream and the tributary were selected representative of pollution gradient and different pollution source. Male adult zebrafish were exposed to surface water from seven sites for 4 days. The obiectives of the study was to evaluate the ability of transcriptomic profiles exposed to surface water to determine the potential biological effects, to differentiate different pollution source, and to identify the toxic components.
2017-04-01 | GSE92330 | GEO
Project description:To assess the impact of surface water across the Hun River, several sampling sites located in the mainstream and the tributary were selected representative of pollution gradient and different pollution source. Male adult zebrafish were exposed to surface water from seven sites for 4 days. The obiectives of the study was to evaluate the ability of transcriptomic profiles exposed to surface water to determine the potential biological effects, to differentiate different pollution source, and to identify the toxic components.
2017-12-19 | GSE108227 | GEO
Project description:The model prokaryote Escherichia coli can exist as a either a commensal or a pathogen in the gut of diverse mammalian hosts. These associations, coupled with its ease of cultivation and genetic variability, have made E. coli a popular indicator organism for tracking the origin of fecal water contamination. Source tracking accuracy is predicated on the assumption that E. coli isolates recovered from contaminated water present a genetic signature characteristic of the host from which they originated. In this study, we compared the accuracy with which E. coli isolated from humans, bear, cattle and deer could be identified by standard fingerprinting methods used for library-based microbial source tracking (repetitive element PCR and pulsed-field gel electrophoresis) in relation to microarray-based analysis of genome content. Our results show that patterns of gene presence or absence were more useful for distinguishing E. coli isolates from different sources than traditional fingerprinting methods, particularly in the case of human strains. Host-associated differences in genome composition included the presence or absence of mobile IS1 elements as well as genes encoding the ferric dicitrate iron transporter (fec), E. coli common pilus (ECP), type 1 fimbriae and the CRISPR associated cas proteins. Many of these differences occurred in regions of the E. coli chromosome previously shown to be M-bM-^@M-^\hot spotsM-bM-^@M-^] for the integration of horizontally-acquired DNA. PCR primers designed to amplify the IS1 and fec loci confirmed array results and demonstrated the ease with which gene presence/absence data can be converted into a diagnostic assay. The data presented here suggest that, despite the high level of genetic diversity observed among isolates by PFGE, human-derived strains may constitute a distinct ecotype distinguished by multiple potential library-independent source tracking markers. Twelve isolates of E. coli ( 3 from bear, 3 from cattle, 3 from deer and 3 from humans) were isolated from feces and/or raw sewage. Genome content for each strain was assessed in duplicate using comparative genome hybridization with E. coli K12 MG1655 as the reference for a total of 24 arrays.
2013-03-01 | E-GEOD-21115 | biostudies-arrayexpress
Project description:Bacteroidetes pyrosequencing for microbial source tracking (MST)
| PRJEB2468 | ENA