Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1020651 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Characterization of microbial communities at the genomic, transcriptomic, proteomic and metabolomic levels, with a special interest on lipid accumulating bacterial populations, which are naturally enriched in biological wastewater treatment systems and may be harnessed for the conversion of mixed lipid substrates (wastewater) into biodiesel. The project aims to elucidate the genetic blueprints and the functional relevance of specific populations within the community. It focuses on within-population genetic and functional heterogeneity, trying to understand how fine-scale variations contribute to differing lipid accumulating phenotypes. Insights from this project will contribute to the understanding the functioning of microbial ecosystems, and improve optimization and modeling strategies for current and future biological wastewater treatment processes. This project contains datasets derived from the same biological wastewater treatment plant. The data includes metagenomes, metatranscriptomes, metaproteomes and organisms isolated in pure cultures. Characterization of microbial communities at the genomic, transcriptomic, proteomic and metabolomic levels, with a special interest on lipid accumulating bacterial populations, which are naturally enriched in biological wastewater treatment systems and may be harnessed for the conversion of mixed lipid substrates (wastewater) into biodiesel. The project aims to elucidate the genetic blueprints and the functional relevance of specific populations within the community. It focuses on within-population genetic and functional heterogeneity, trying to understand how fine-scale variations contribute to differing lipid accumulating phenotypes. Insights from this project will contribute to the understanding the functioning of microbial ecosystems, and improve optimization and modeling strategies for current and future biological wastewater treatment processes. This project contains datasets derived from the same biological wastewater treatment plant. The data includes metagenomes, metatranscriptomes, metaproteomes and organisms isolated in pure cultures.
2020-08-19 | PXD013655 | Pride
Project description:To understand microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and the effects of environmental factors on their structure, 12 activated sludge samples were collected from four WWTPs in Beijing. GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes. The results showed that, for each gene category, such as egl, amyA, nir, ppx, dsrA sox and benAB, there were a number of microorganisms shared by all 12 samples, suggestive of the presence of a core microbial community in the activated sludge of four WWTPs. Variance partitioning analyses (VPA) showed that a total of 53% of microbial community variation can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs. Four full-scale wastewater treatment systems located in Beijing were investigated. Triplicate samples were collected in each site.
2014-01-15 | E-GEOD-54055 | biostudies-arrayexpress
Project description:Bio-augmentation could be a promising strategy to improve processes for treatment and resource recovery from wastewater. In this study, the Gram-positive bacterium Bacillus subtilis was co-cultured with the microbial communities present in wastewater samples with high concentrations of nitrate or ammonium. Glucose supplementation (1%) was used to boost biomass growth in all wastewater samples. In anaerobic conditions, the indigenous microbial community bio-augmented with B. subtilis was able to rapidly remove nitrate from wastewater. In these conditions, B. subtilis overexpressed nitrogen assimilatory and respiratory genes including NasD, NasE, NarG, NarH, and NarI, which arguably accounted for the observed boost in denitrification. Next, we attempted to use the the ammonium- and nitrate-enriched wastewater samples bio-augmented with B. subtilis in the cathodic compartment of bioelectrochemical systems (BES) operated in anaerobic condition. B. subtilis only had low relative abundance in the microbial community, but bio-augmentation promoted the growth of Clostridium butyricum and C. beijerinckii, which became the dominant species. Both bio-augmentation with B. subtilis and electrical current from the cathode in the BES promoted butyrate production during fermentation of glucose. A concentration of 3.4 g/L butyrate was reached with a combination of cathodic current and bio-augmentation in ammonium-enriched wastewater. With nitrate-enriched wastewater, the BES effectively removed nitrate reaching 3.2 mg/L after 48 h. In addition, 3.9 g/L butyrate was produced. We propose that bio-augmentation of wastewater with B. subtilis in combination with bioelectrochemical processes could both boost denitrification in nitrate-containing wastewater and enable commercial production of butyrate from carbohydrate- containing wastewater, e.g. dairy industry discharges. These results suggest that B. subtilis bio-augmentation in our BES promotes simultaneous wastewater treatment and butyrate production.
2020-05-15 | GSE150480 | GEO
Project description:In this study, we exposed Caenorhabditis elegans wild types N2 to water collected from six sources in the Dutch village Sneek. The sources were: wastewater from a hospital, a community (80 households), a nursing home, influent into the local municipal wastewater treatment plant, effluent of the wastewater treatment plant, and surface water samples. The goal of the experiment was to determine if C. elegans can be used to identify pollutants in the water by transcriptional profiling. Age synchronized worms at developmental L4 larval stage were exposed to treatment for 24 hours. After flash freezing the samples, RNA was isolated, labeled and hybridized on oligo microarray (Agilent) slides.
2022-12-03 | E-MTAB-11260 | biostudies-arrayexpress
Project description:To understand microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and the effects of environmental factors on their structure, 12 activated sludge samples were collected from four WWTPs in Beijing. GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes. The results showed that, for each gene category, such as egl, amyA, nir, ppx, dsrA sox and benAB, there were a number of microorganisms shared by all 12 samples, suggestive of the presence of a core microbial community in the activated sludge of four WWTPs. Variance partitioning analyses (VPA) showed that a total of 53% of microbial community variation can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs.
2014-01-15 | GSE54055 | GEO
Project description:The ammonia-oxidizing bacterium Nitrosomonas europaea has been widely recognized as an important player in the nitrogen cycle as well as one of the most abundant members in microbial communities for the treatment of industrial or sewage wastewater. Its natural metabolic versatility and extraordinary ability to degrade environmental pollutants enable it to thrive under various harsh environmental conditions. This model of N. europaea (iGC535) is the most accurate metabolic model for a nitrifying organism to date, reaching an average prediction accuracy of over 90% under several growth conditions. The manually curated model can predict phenotypes under chemolithotrophic and chemolithoorganotrophic conditions while oxidating methane and wastewater pollutants.
It is the first upload of the model.
2024-09-02 | BIOMD0000001061 | BioModels