May 10, 2014 - Yu Xia & Xiaohui Wang & Xianghua Wen & Kun Ding &. Jizhong Zhou & Yunfeng Yang & Yu Zhang. Received: 10 December 2013 /Revised: ...
Overall functional gene diversity of microbial communities in three full-scale activated sludge bioreactors Yu Xia, Xiaohui Wang, Xianghua Wen, Kun Ding, Jizhong Zhou, Yunfeng Yang & Yu Zhang Applied Microbiology and Biotechnology ISSN 0175-7598 Volume 98 Number 16 Appl Microbiol Biotechnol (2014) 98:7233-7242 DOI 10.1007/s00253-014-5791-7
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Author's personal copy Appl Microbiol Biotechnol (2014) 98:7233–7242 DOI 10.1007/s00253-014-5791-7
ENVIRONMENTAL BIOTECHNOLOGY
Overall functional gene diversity of microbial communities in three full-scale activated sludge bioreactors Yu Xia & Xiaohui Wang & Xianghua Wen & Kun Ding & Jizhong Zhou & Yunfeng Yang & Yu Zhang
Received: 10 December 2013 / Revised: 25 April 2014 / Accepted: 26 April 2014 / Published online: 10 May 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Understanding microbial community composition is thought to be crucial for improving process functioning and stabilities of full-scale activated sludge reactors in wastewater treatment plants (WWTPs). However, functional gene compositions of microbial communities within them have not been clearly elucidated. To gain a complete picture of microbial community, in this study, GeoChip 4.2 was used to profile the overall functional genes of three full-scale activated sludge bioreactors, the 16S rRNA gene diversities of which had been unveiled by 454-pyrosequencing in our previous investigation. Triplicate activated sludge samples from each system were analyzed, with the detection of 38,507 to 40,654 functional genes. A high similarity of 77.3–81.2 % shared functional genes was noted among the nine samples, verified by the high 16S rRNA gene similarity with shared operational
taxonomic units (OTUs) constituting 66.4–70.0 % of the detected sequences in each system. Correlation analyses showed that the abundances of a wide array of functional genes were associated with system performances. For example, the abundances of carbon degradation genes were strongly correlated to chemical oxygen demand (COD) removal efficiencies (r=0.8697, P
