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.
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.
Project description:Wastewater treatment plants use a variety of bioreactor types and configurations to remove organic matter and nutrients. Little is known regarding the effects of different configurations and within-plant immigration on microbial community dynamics. Previously, we found that the structure of ammonia-oxidizing bacterial (AOB) communities in a full-scale dispersed growth activated sludge bioreactor correlated strongly with levels of NO2- entering the reactor from an upstream trickling filter (Wells et al 2009). Here, to further examine this puzzling association, we profile within-plant microbial biogeography (spatial variation) and test the hypothesis that substantial microbial immigration occurs along a transect (raw influent, trickling filter biofilm, trickling filter effluent, and activated sludge) at the same full-scale wastewater treatment plant. AOB amoA gene abundance increased >30-fold between influent and trickling filter effluent concomitant with NO2- production, indicating unexpected growth and activity of AOB within the trickling filter. Nitrosomonas europaea was the dominant AOB phylotype in trickling filter biofilm and effluent, while a distinct ‘Nitrosomonas-like’ lineage dominated in activated sludge. Prior time series indicated that this ‘Nitrosomonas-like’ lineage was dominant when NO2- levels in the trickling filter effluent (i.e., activated sludge influent) were low, while N. europaea became dominant in the activated sludge when NO2- levels were high. This is consistent with the hypothesis that NO2- production may co-occur with biofilm sloughing, releasing N. europaea from the trickling filter into the activated sludge bioreactor. Phylogenetic microarray (PhyloChip) analyses revealed significant spatial variation in taxonomic diversity, including a large excess of methanogens in the trickling filter relative to activated sludge and attenuation of Enterobacteriaceae across the transect, and demonstrated transport of a highly diverse microbial community via the trickling filter effluent to the activated sludge bioreactor. Our results provide compelling evidence that substantial immigration between coupled process units occurs and may exert significant influence over microbial community dynamics within staged bioreactors.
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.
Project description:Dissimilatory nitrate reduction to ammonia (DNRA) is an important part of the microbial N-cycle both in natural and man-made habitats, although its significance in wastewater treatment plants is not well understood. Nitrate-limited enrichments from activated sludge with acetate as e-donor consistently resulted in a domination of two closely related genotypes of ammonifying members of Deltaproteobacteria belonging to the genus Geobacter. One of the two was isolated in pure culture which appears to be an extremely specialized ammonifier, actively growing only with acetate as e-donor and C source and nitrate as e-acceptor. The shotgun proteomic raw data obtained from whole cell lysates are provided. First and corresponding author: Dimitry Y. Sorokin soroc@inmi.ru; d.sorokin@tudelft.nl
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.