Dataset Information

Overall functional diversity of microbial communities in three full-scale activated sludge bioreactors

ABSTRACT: 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.

ORGANISM(S): Archaea Eukaryota Bacteria activated sludge metagenome Viruses

PROVIDER: GSE53744 | GEO | 2014/12/31

SECONDARY ACCESSION(S): PRJNA232777

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

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.

Project description:Fire disturbances are becoming more common, more intense, and further-reaching across the globe, with consequences for ecosystem functioning. Importantly, fire can have strong effects on the soil microbiome, including community and functional changes after fire, but surprisingly little is known regarding the role of soil fire legacy in shaping responses to recent fire. To address this gap, we conducted a manipulative field experiment administering fire across 32 soils with varying fire legacies, including combinations of 1-7 historic fires and 1-33 years since most recent fire. We analyzed soil metatranscriptomes, determining for the first time how fire and fire legacy interactively affect metabolically-active soil taxa, the microbial regulation of important carbon (C), nitrogen (N) and phosphorus (P) cycling, expression of carbohydrate-cycling enzyme pathways, and functional gene co-expression networks. Experimental fire strongly downregulated fungal activity while upregulating many bacterial and archaeal phyla. Further, fire decreased soil capacity for microbial C and N cycling and P transport, and drastically rewired functional gene co-expression. Perhaps most importantly, we highlight a novel role of soil fire legacy in regulation of microbial C, N, and P responses to recent fire. We observed a greater number of functional genes responsive to the interactive effects of fire and fire legacy than those affected solely by recent fire, indicating that many functional genes respond to fire only under certain fire legacy contexts. Therefore, without incorporating fire legacy of soils, studies will miss important ways that fire shapes microbial roles in ecosystem functioning. Finally, we showed that fire caused significant downregulation of carbon metabolism and nutrient cycling genes in microbiomes under abnormal soil fire histories, producing a novel warning for the future: human manipulation of fire legacies, either indirectly through global change-induced fire intensification or directly through fire suppression, can negatively impact soil microbiome functional responses to new fires.

Dataset Information

Overall functional diversity of microbial communities in three full-scale activated sludge bioreactors

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets