Ontology highlight
ABSTRACT:
PROVIDER: PRJNA555822 | ENA |
REPOSITORIES: ENA
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:Understanding microbial community diversity is thought to be crucial for improving process functioning and stabilities of wastewater treatment systems. However, current studies largely focus on taxonomic groups based on 16S rRNA, which are not necessarily linked to functioning, or a few selected functional genes. Here we launched a study to profile the overall functional genes of microbial communities in three full-scale wastewater treatment systems. Triplicate activated sludge samples from each system were analyzed using a high-throughput metagenomics tool named GeoChip 4.2, resulting in the detection of 38,507 to 40,647 functional genes. A high similarity of 75.5% to 79.7% shared genes was noted among the nine samples. Moreover, correlation analyses showed that the abundances of a wide array of functional genes were associated with system performances. For example, the abundances of overall nitrogen cycling genes had a strong correlation to total nitrogen (TN) removal rates (r = 0.7647, P < 0.01). The abundances of overall carbon cycling genes were moderately correlated with COD removal rates (r = 0.6515, P < 0.01). Lastly, we found that influent chemical oxygen demand (COD inf) and total phosphorus concentrations (TP inf), and dissolved oxygen (DO) concentrations were key environmental factors shaping the overall functional genes. Together, the results revealed vast functional gene diversity and some links between the functional gene compositions and microbe-mediated processes.
2014-12-31 | GSE53744 | GEO
Project description:Understanding and quantifying the effects of environmental factors influencing the variation of abundance and diversity of microbial communities was a key theme of ecology. For microbial communities, there were two factors proposed in explaining the variation in current theory, which were contemporary environmental heterogeneity and historical events. Here, we report a study to profile soil microbial structure, which infers functional roles of microbial communities, along the latitudinal gradient from the north to the south in China mainland, aiming to explore potential microbial responses to external condition, especially for global climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 5.0, we showed that microbial communities were distinct for most but not all of the sites. Using substantial statistical analyses, exploring the dominant factor in influencing the soil microbial communities along the latitudinal gradient. Substantial variations were apparent in nutrient cycling genes, but they were in line with the functional roles of these genes. 300 samples were collected from 30 sites along the latitudinal gradient, with 10 replicates in every site
2015-05-23 | E-GEOD-69171 | biostudies-arrayexpress
Project description:Exploration of Environmental Virome and Functional metagenomics
| PRJEB42516 | ENA
Project description:Understanding biological diversity and distribution patterns at multiple spatial scales is a central issue in ecology. Here, we investigated the biogeographical patterns of functional genes in soil microbes from 24 arctic heath sites using GeoChip-based metagenomics and principal coordinates of neighbour matrices (PCNM)-based analysis. Functional gene richness varied considerably among sites, while the proportions of each major functional gene category were evenly distributed. Functional gene composition varied significantly at most medium and broad spatial scales, and the PCNM analyses indicated that 14-20% of the variation in total and major functional gene categories could be attributed primarily to relatively broad-scale spatial effects that were consistent with broad-scale variation in soil pH and total nitrogen. The combination of variance partitioning and multi-scales analysis indicated that spatial distance effects contributed 12% to variation in functional gene composition，whereas environmental factors contributed only 3%. This relatively strong influence of spatial as compared to environmental variation in determining functional gene distributions contrasts sharply with typical microbial phylotype/species-based biogeographical patterns in the Arctic and elsewhere. Our results suggest that the distributions of soil functional genes cannot be predicted from phylogenetic distributions because spatial factors associated with historical contingencies are relatively important determinants of their biogeography.
2014-12-10 | GSE63927 | GEO
Project description:Huanglongbing (HLB) is a worldwide devastating disease of citrus. There are no effective control measures for this newly emerging but century-old disease. A powerful oligonucleotide microarray of high-density 16S rRNA genes, the PhyloChip microarray, has been developed and effectively used to study bacterial diversity, especially from environmental samples. In this article, we aim to decipher the bacterial microbiome in HLB-affected citrus versus non-infected citrus as well as in citrus plants treated with ampicillin and gentamicin using PhyloChip-based metagenomics.
2013-05-09 | GSE46728 | GEO
Project description:Here, we applied a microarray-based metagenomics technology termed GeoChip 5.0 to investigate spring microbial functional genes in mesocosm-simulated shallow lake ecosystems having been undergoing nutrient enrichment and warming for nine years.
2020-12-30 | GSE155582 | GEO
Project description:Microbiome host model is a Named Entity Recognition (NER) model that identifies and annotates the host of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with host metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2022-02-21 | MODEL2202170006 | BioModels
Project description:Microbiome ecoregion model is a Named Entity Recognition (NER) model that identifies and annotates the ecoregion of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with ecoregion metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2023-09-15 | MODEL2202170003 | BioModels
Project description:Microbiome site model is a Named Entity Recognition (NER) model that identifies and annotates the site of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with site metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2023-09-15 | MODEL2202170013 | BioModels