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This dissertation, Exploring Biodegradation of Emerging Pollutants Using Next Generation Sequencing and UPLC-MS-MS Techniques by Ke, Yu, 余珂, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: This study was conducted to set up a systematic approach utilizing advantages of both wet lab and bioinformatic methodologies to study biodegradation abilities and microbial bacterial-functional relationship within bioremediation communities. Firstly, 11pharmaceuticals and personal care products (PPCPs)were selected as target chemicals for establishing an effective determination process in analyzing trace-level concentrations in the environment, and understanding the removal routes during pollutants removal process in wastewater treatment process using activated sludge. Ultra performance liquid chromatography-tandem mass spectrometry was utilized to develop a rapid, sensitive and reliable method without solid phase extraction pre-concentration for trace analysis of 11 PPCPs in influent and effluent from municipal wastewater treatment plants. Shorten the detection time and significant reduction of detection cost were achieved due to the omitting usage of solid phase extraction (SPE)process and avoiding the consumption of hydrophiliclipophilic balancced (HLB)cartridge. Research on removal routes of ten selected PPCPs in activated sludge found activated sludge hardly removed carbamazepine. Biodegradation was the sole route to remove acyclovir, metronidazole, benzylparaben, ethylparaben, methylparaben and propylparaben. Both adsorption and biodegradation were involved in the removal of ranitidine and benzophenone-3, while fluoxetine could be totally removed by adsorption in activated sludge. Secondly, as the target microbial community, activated sludge community was used to set up the global bioinformatic analysis process. Both metagenomic and metatranscriptomic approaches were processed to characterize microbial structure and gene expression of activated sludge community. The taxonomic profile showed thatactivated sludge was dominated by Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Verrucomicrobiaphyla. Gene expression annotation of nitrogen removal revealed that denitrification-related genes sequences dominated in both DNA and cDNA datasets while nitrifying genes were also expressed in relative high levels. Specially, ammonia monooxygenase and hydroxylamine oxidase demonstrated the high cDNA/DNA ratios, indicating strong nitrification activity. Ammonia-oxidizing bacteria present mainly belonged to Nitrosomonas and Nitrosospira species. A fast method to construct local sub-databases has been established for the quick similarity search and annotation of huge metagenomic datasets. The conducted tests showed sub-database annotation pipeline achieved a speedup of 150-385 times, and got exactly the same annotation results with those of the direct NCBI-nr database BLAST-MEGAN method. This approach provides a new time-efficient and convenient annotation similarity search strategy for laboratories without access to high performance computing facilities. Thirdly, bisphenol A(BPA), which has a partially known biodegradation pathway and relevant bioremediating genes, was chosen as a model to establish a pipeline for systematical understanding the pathways and gene/bacteria relationships in an enriched microbial community. 11 new metabolites were detected during BPA degradation. Thereby, a novel pathway of degrading BPA metabolite was proposed. Sphingomonas strains were dominant taxa in initial degradation of BPA, while the other

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