Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1031677 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Membrane bioreactor (MBR) systems are typically known different from conventional activated sludge (CAS) systems in operational parameters, while current knowledge of their microbial differentiations is barely sufficient. To this end, the current study was launched to address the differences of the overall functional genes of an oxidation ditch (OD) and an MBR running parallelly at full-scale using a functional gene array-GeoChip 4.2. Two full-scale wastewater treatment systems applying the processes of oxidation ditch (OD) and membrane bioreactor (MBR) were investigated. They treated identical wastewater at the same scale. 12 mixed-liquor suspended sludge (MLSS) samples collected daily on 12 consecutive days from each system were analyzed by GeoChip 4.2.
2016-03-01 | E-GEOD-67307 | biostudies-arrayexpress
Project description:Limited systems-level understanding of CO2 concentrating mechanism (CCM) and metabolic adaption in response to different CO2-level in wild oleaginous algae has hindered the development of microalgal feedstock and the knowledge of its role in global warming and oceanic acidification. Nannochloropsis are a group of small unicellular microalgae widely distributed in oceans and fresh water, which implies that it plays a crucial role in biogeochemical cycles impinged on global climate change. In addition, Nannochloropsis has been used for flue gas fixation in many large-scale and pilot-scale outdoor cultivation facilities for photosynthetic production of fuels and chemicals. To untangle the intricate genome-wide networks underlying CCM and metabolic adjustment under different CO2 concentrations in Nannochloropsis, we applied high-throughput mRNA-sequencing and reconstructed the structure and dynamics of the genome-wide functional network underlying robust microalgal CCM and in Nannochloropsis oceanica, by tracking the genome-wide, single-base-resolution transcript change for the complete time-courses of different CO2 concentrations.
2019-07-16 | GSE55861 | GEO
Project description:Mixed method metagenome of a full-scale biogas facility collected over 19 months
| PRJNA1180090 | ENA
Project description:Limited systems-level understanding of oil synthesis in wild oleaginous algae has hindered the development of microalgal feedstock. Nannochloropsis is a small unicellular microalgae widely distributed in oceans and fresh water. In many large-scale and pilot-scale outdoor cultivation facilities, Nannochloropsis strains have been found to be capable of robust growth when supplied with flue gases, naturally accumulating large quantities of oils in a stationary phase, and exhibiting resistance to environmental contaminants. The rich genomic resources, compact genomes, resistance to foreign DNA invasion, wide ecological adaptation, large collections of natural strains and the demonstrated ability to grow on a large scale suggested Nannochloropsis can serve as research models and platform strains for economical and scalable photosynthetic production of fuels and chemicals. To untangle the intricate genome-wide networks underlying the robust biomass accumulation and oil production in Nannochloropsis, we applied high-throughput mRNA-sequencing and reconstructed the structure and dynamics of the genome-wide functional network underlying robust microalgal triacylglycerol (TAG) production in Nannochloropsis oceanica, by tracking the genome-wide, single-base-resolutiontranscript change for the complete time-courses of nitrogen-depletion-induced TAG synthesis.
2014-05-14 | GSE42508 | GEO
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:Predicting microbial community structure and dynamics in full-scale wastewater treatment plants by using graph neural network models
| PRJNA1021975 | ENA
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:Chloroflexota in full-scale wastewater treatment plants
| PRJEB72889 | ENA