Wastewater metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA524094 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR11070500_1.fastq.gz | Fastqsanger.gz | |||
| SRR11070500_2.fastq.gz | Fastqsanger.gz | |||
| SRR11070600_1.fastq.gz | Fastqsanger.gz | |||
| SRR11070600_2.fastq.gz | Fastqsanger.gz |
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Project description:Municipal wastewater effluent can impact its receiving environment. In the St. Lawrence River, male fish living downstream from Montreal exhibit increased hepatic vitellogenin, intersex, delayed spermatogenesis and altered immune function. Few studies have examined genome-wide effects associated with municipal effluent exposure in fish to decipher the mechanisms of toxicity. The present objective was to identify hepatic cellular signaling pathways in fathead minnows following exposure to municipal wastewater effluent. Immature minnows were exposed for 21 days to either 0% (Control) or 20% municipal effluent, the highest concentration in the St. Lawrence River. Hepatic RNA was extracted and used to hybridize a fathead minnow oligonucleotide microarray containing approximately 15K gene sequences.
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Project description:Municipal wastewater effluent can impact its receiving environment. In the St. Lawrence River, male fish living downstream from Montreal exhibit increased hepatic vitellogenin, intersex, delayed spermatogenesis and altered immune function. Few studies have examined genome-wide effects associated with municipal effluent exposure in fish to decipher the mechanisms of toxicity. The present objective was to identify hepatic cellular signaling pathways in fathead minnows following exposure to municipal wastewater effluent. Immature minnows were exposed for 21 days to either 0% (Control) or 20% municipal effluent, the highest concentration in the St. Lawrence River. Hepatic RNA was extracted and used to hybridize a fathead minnow oligonucleotide microarray containing approximately 15K gene sequences. Sixteen samples were examined, 8 control samples and 8 exposed samples.
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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.
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