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Exploring microbial community structures and functions of activated sludge by high-throughput sequencing

To investigate the diversities and abundances of nitrifiers and to apply the highthroughput

sequencing technologies to analyze the overall microbial community

structures and functions in the wastewater treatment bioreactors were the major

objectives of this study. Specifically, this study was conducted: (1) to investigate the

diversities and abundances of AOA, AOB and NOB in bioreactors, (2) to explore the

bacterial communities in bioreactors using 454 pyrosequencing, and (3) to analyze the

metagenomes of activated sludge using Illumina sequencing.

A lab-scale nitrification bioreactor was operated for 342 days under low DO (0.15~0.5

mg/L) and high nitrogen loading (0.26~0.52 kg-N/(m3d)). T-RFLP and cloning analysis

showed there were only one dominant AOA, AOB and NOB species in the bioreactor,

respectively. The amoA gene of the dominant AOA had a similarity of 89.3% with the

isolated AOA species Nitrosopumilus maritimus SCM1. The AOB species detected in the

bioreactor belonged to Nitrosomonas genus. The abundance of AOB was more than 40

times larger than that of AOA. The percentage of NOB in total bacteria increased from

not detectable to 30% when DO changed from 0.15 to 0.5 mg/L. Compared with

traditional methods, pyrosequencing analysis of the bacteria in this bioreactor provided

unprecedented information. 494 bacterial OTUs was obtained at 3% distance cutoff.

Furthermore, 454 pyrosequencing was applied to investigate the bacterial communities of

activated sludge samples from 14 WWTPs of Asia (mainland China, Hong Kong, and

Singapore) and North America (Canada and the United States). The results revealed huge

amounts of OTUs in activated sludge, i.e. 1183~3567 OTUs in one sludge sample at 3%

distance cutoff. Clear geographical differences among these samples were observed. The

AOB amoA genes in different WWTPs were found quite diverse while the 16S rRNA

genes were relatively conserved.

To explore microbial community structures and functions in the abovementioned labscale

bioreactor and a full-scale bioreactor, over six gigabases of metagenomic sequence

data and 150,000 paired-end reads of PCR amplicons were generated from the activated

sludge in the two bioreactors on Illumina HiSeq2000 platform. Three kinds of sequences

(16S rRNA amplicons, 16S rRNA gene tags and predicted genes) were used to conduct

taxonomic assignment and their applicabilities and reliabilities were compared. Specially,

based on 16S rRNA and amoA gene sequences, AOB were found more abundant than

AOA in the two bioreactors. Furthermore, the analysis of the metabolic profiles and

pathways indicated that the overall pathways in the two bioreactors were quite similar.

However, the abundances of some specific genes in the two bioreactors were different.

In addition, 454 pyrosequencing was also used to detect potentially pathogenic bacteria in

environmental samples. It was found most abundant potentially pathogenic bacteria in the

WWTPs were affiliated with Aeromonas and Clostridium. Aeromonas veronii,

Aeromonas hydrophila and Clostridium perfringens were species most similar to the

potentially pathogenic bacteria found in this study. Overall, the percentage of the

sequences closely related to known pathogenic bacteria sequences was about 0.16% of

the total sequences. Additionally, a Java application (BAND) was developed for

graphical visualization of microbial abundance data. / published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

Identiferoai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/184237
Date January 2012
CreatorsYe, Lin, 叶林
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Source SetsHong Kong University Theses
LanguageEnglish
Detected LanguageEnglish
TypePG_Thesis
Sourcehttp://hub.hku.hk/bib/B48079649
RightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License
RelationHKU Theses Online (HKUTO)

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