Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1178615 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31159405_1.fastq.gz | Fastqsanger.gz | |||
| SRR31159405_2.fastq.gz | Fastqsanger.gz | |||
| SRR31159406_1.fastq.gz | Fastqsanger.gz | |||
| SRR31159406_2.fastq.gz | Fastqsanger.gz | |||
| SRR31159407_1.fastq.gz | Fastqsanger.gz |
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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: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.
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Project description:Israel Pilot-Scale Hospital Wastewater Treatment System Raw sequence reads
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Project description:We developed a laboratory-scale model to improve our understanding and capacity to assess the biological risks of genetically engineered bacteria and their genetic elements in the natural environment. Our hypothetical scenario concerns an industrial bioreactor failure resulting in the introduction of genetically engineered bacteria to a downstream municipal wastewater treatment plant (MWWTP). As the first step towards developing a model for this scenario, we sampled microbial communities from the aeration basin of a MWWTP at three seasonal time points. Having established a baseline for community composition, we investigated how the community changed when propagated in the laboratory, including cell culture media conditions that could provide selective pressure in future studies. Specifically, using PhyloChip 16S rRNA gene-targeting microarrays, we compared the compositions of sampled communities to those of inoculates propagated in the laboratory in simulated wastewater conditionally amended with various carbon sources (glucose, chloroacetate, D-threonine) or the ionic liquid 1-ethyl-3-methylimidazolium chloride ([C2mim]Cl). Proteobacteria, Bacteroidetes, and Actinobacteria were predominant in aeration basin and laboratory-cultured populations. Laboratory-cultured populations were enriched in Gammaproteobacteria. Enterobacteriaceae and Aeromonadaceae were enriched by glucose, Pseudomonadaceae by chloroacetate and D-threonine, and Burkholderiaceae by high (50 mM) concentrations of chloroacetate. Microbial populations cultured with chloroacetate and D-threonine were more similar to sampled populations than thoes cultured with glucose or [C2mim]Cl. Although observed relative richness in operational taxonomic units was lower for laboratory cultures than for sampled populations, both flask and reactor systems cultured phylogenetically diverse communities. These results importantly provide a foundation for laboratory models of industrial bioreactor failure scenarios.
2014-06-06 | GSE58251 | GEO
Project description:We developed a laboratory-scale model to improve our understanding and capacity to assess the biological risks of genetically engineered bacteria and their genetic elements in the natural environment. Our hypothetical scenario concerns an industrial bioreactor failure resulting in the introduction of genetically engineered bacteria to a downstream municipal wastewater treatment plant (MWWTP). As the first step towards developing a model for this scenario, we sampled microbial communities from the aeration basin of a MWWTP at three seasonal time points. Having established a baseline for community composition, we investigated how the community changed when propagated in the laboratory, including cell culture media conditions that could provide selective pressure in future studies. Specifically, using PhyloChip 16S rRNA gene-targeting microarrays, we compared the compositions of sampled communities to those of inoculates propagated in the laboratory in simulated wastewater conditionally amended with various carbon sources (glucose, chloroacetate, D-threonine) or the ionic liquid 1-ethyl-3-methylimidazolium chloride ([C2mim]Cl). Proteobacteria, Bacteroidetes, and Actinobacteria were predominant in aeration basin and laboratory-cultured populations. Laboratory-cultured populations were enriched in Gammaproteobacteria. Enterobacteriaceae and Aeromonadaceae were enriched by glucose, Pseudomonadaceae by chloroacetate and D-threonine, and Burkholderiaceae by high (50 mM) concentrations of chloroacetate. Microbial populations cultured with chloroacetate and D-threonine were more similar to sampled populations than thoes cultured with glucose or [C2mim]Cl. Although observed relative richness in operational taxonomic units was lower for laboratory cultures than for sampled populations, both flask and reactor systems cultured phylogenetically diverse communities. These results importantly provide a foundation for laboratory models of industrial bioreactor failure scenarios. 46 samples, flask and reactor experiments were conducted in triplicate with two exceptions: [C2mim]Cl_flask and No-Carbon_flask treatments had only one sample (no replicates).
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Project description:Objective. To identify gene expression differences in peripheral blood from patients with early and late onset juvenile idiopathic arthritis (JIA). Methods. Peripheral blood mononuclear cells (PBMC) were isolated from 56 healthy controls and 104 patients with recent onset JIA (39 persistent oligoarticular, 45 RF-polyarticular, and 20 systemic). Poly(A) RNA was amplified and labeled using NuGEN Ovation, and gene expression assessed with Affymetrix HG-U133 Plus 2.0 GeneChips®. Results. A total of 832 probe sets revealed gene expression differences (false-discovery rate 5%) in PBMC from children with oligoarticular JIA whose disease began before 6 years of age (age at onset [AaO] <6; early onset), compared to subjects whose disease began at 6 years of age or later (AaO ≥6; late onset). In early onset patients there was greater expression of genes related to B-cells, and lesser expression of genes related to cells of the myeloid lineage. Support Vector Machine algorithms identified samples from early or late onset oligoarticular (97% accuracy) or polyarticular (89% accuracy) JIA patients, but not systemic JIA patients or healthy controls. Principal component analysis showed that the major classifier of samples was AaO regardless of whether they had oligoarticular or polyarticular JIA. Conclusion. PBMC gene expression analysis reveals biologic differences between early and late onset JIA patients independent of classification based on the number of joints involved. These data suggest AaO may be an important parameter to consider in JIA classification. Furthermore, different pathologic mechanisms may influence AaO, and understanding these processes may lead to improved treatment of JIA.
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