scholarly journals Effect of Aeration Rates and Filter Media Heights on the Performance of Pollutant Removal in an Up-Flow Biological Aerated Filter

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1244 ◽  
Author(s):  
Jiehui Ren ◽  
Wen Cheng ◽  
Tian Wan ◽  
Min Wang ◽  
Chengcheng Zhang
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Relative Abundance ◽  
Microbial Community Structure ◽  
Municipal Wastewater ◽  
Biological Aerated Filter ◽  
Filter Media ◽  
N Removal ◽  
Pollutants Removal ◽  
Aerated Filter

The biological aerated filter (BAF) is an effective biological treatment technology which removes the pollutants in municipal wastewater secondary treatment. However, we still know little about the interaction between the pollutants removal and microbes within the BAF. In this study, we used an up-flow BAF (UBAF) reactor to investigate the relationships between the pollutants removal and microbial community structure at different aeration rates and filter media heights. The microbial community of biofilm was analyzed by Illumina pyrosequencing. Our results showed that the UBAF achieved a better removal efficiency of chemical oxygen demand (COD), NH4+-N, NO3−-N, and total phosphorus (TP) at an aeration rate of 65 L/h. In addition, the COD and NH4+-N removal mainly occurred at 0–25 cm height of filter media. The microbial community structure in the UBAF demonstrated that the relative abundance of the Planctomycetes and Comamonadaceae at 10 cm height of filter media were 11% and 48.1%, respectively, proportions significantly higher than those under others treatments. Finally, the changes in relative abundance of Proteobacteria, Planctomycetes, and Nitrospirae likely explained the mechanism of nitrogen and phosphorus removal. Our results showed that suitable conditions could enhance the microbial community structure to achieve a high pollutants removal in the UBAF.

scholarly journals Simulation-based approaches to characterize metagenome coverage as a function of sequencing effort and microbial community structure

2018 ◽  
Author(s):  
Taylor Royalty ◽  
Andrew D. Steen
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Genome Size ◽  
Relative Abundance ◽  
Microbial Community Structure ◽  
Software Tool ◽  
Individual Genome ◽  
Base Pairs ◽  
Simulation Based ◽  
Sequencing Experiment

AbstractWe applied simulation-based approaches to characterize how microbial community structure influences the amount of sequencing effort to reconstruct metagenomes that are assembled from short read sequences. An initial analysis evaluated the quantity, completion, and contamination of complete-metagenome-assembled genome (complete-MAG) equivalents, a bioinformatic-pipeline normalized metric for MAG quantity, as a function of sequencing effort, on four preexisting sequence read datasets taken from a maize soil, an estuarine sediment, the surface ocean, and the human gut. These datasets were subsampled to varying degrees of completeness in order to simulate the effect of sequencing effort on MAG retrieval. Modeling suggested that sequencing efforts beyond what is typical in published experiments (1 to 10 Gbp) would generate diminishing returns in terms of MAG binning. A second analysis explored the theoretical relationship between sequencing effort and the proportion of available metagenomic DNA sequenced during a sequencing experiment as a function of community richness, evenness, and genome size. Simulations from this analysis demonstrated that while community richness and evenness influenced the amount of sequencing required to sequence a community metagenome to exhaustion, the effort necessary to sequence an individual genome to a target fraction of exhaustion was only dependent on the relative abundance of the corresponding organism and its genome size. A software tool, GRASE, was created to assist investigators further explore this relationship. Re-evaluation of the relationship between sequencing effort and binning success in the context of the relative abundance of genomes, as opposed to base pairs, provides a framework to design sequencing experiments based on the relative abundance of microbes in an environment rather than arbitrary levels of sequencing effort.

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