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GeoChip-based analysis of the microbial community functional structures in simultaneous desulfurization and denitrification process
作者姓名:Hao Yu  Chuan Chen  Jincai M  Wenzong Liu  Jizhong Zhou  Duu-Jong Lee  Nanqi Ren  Aijie Wang
作者单位:School of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA;Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;Institute for Environmental Genomics, Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA;Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
基金项目:This work was supported by the National High-Tech Research and Development Program (863) of China (No. 2011AA060904), and the National Natural Science Foundation of China (Nos. 51111140388, 51176037).
摘    要:The elemental sulfur (S^0) recover), was evaluated in the presence of hi,ate in two development models of simultaneous desulfurization and denitrification (SDD) process. At the loading rates of 0.9 kg S/(m^3.day) for sulfide and 0.4 kg N/(m^3.day) for nitrate, SO conversion rate was 91.1% in denitrifying sulfide removal (DSR) model which was higher than in integrated simultaneous desulfurization and denitrification (ISDD) model (25.6%). A comprehensive analysis of functional diversity, structure and metabolic potential of microbial communities was examined in two models by using functional gene array (GeoChip 2.0). GeoChip data indicated that diversity indices, community structure, and abundance of functional genes were distinct between two models. Diversity indices (Simpson's diversity index (1/D) and Shannon-Weaver index (H′)) of all detected genes showed that with elevated infiuent loading rate, the functional diversity decreased in ISDD model but increased in DSR model. In contrast to ISDD model, the overall abundance of dsr genes was lower in DSR model, while some functional genes targeting from nitrate-reducing sulfide-oxidizingbacteria {NR-SOB), such as Thiobacillus denitrficans, Sulfurimonas denitrificans, and Paracoccus pantotrophus were more abundant in DSR model which were highly associated with the change of SO conversion rate obtained in two models. The results obtained in this study provide additional insights into the microbial metabolic mechanisms involved in ISDD and DSR models, which in turn will improve the overall performance of SDD process.

关 键 词:微生物群落  脱硫脱硝  功能结构  脱硝工艺  物种多样性指数  功能基因  基础  硫转化率
收稿时间:19 August 2013
修稿时间:2 December 2013

GeoChip-based analysis of the microbial community functional structures in simultaneous desulfurization and denitrification process
Hao Yu,Chuan Chen,Jincai M,Wenzong Liu,Jizhong Zhou,Duu-Jong Lee,Nanqi Ren,Aijie Wang.GeoChip-based analysis of the microbial community functional structures in simultaneous desulfurization and denitrification process[J].Journal of Environmental Sciences,2014,26(7):1375-1382.
Authors:Hao Yu  Chuan Chen  Jincai M  Wenzong Liu  Jizhong Zhou  Duu-Jong Lee  Nanqi Ren and Aijie Wang
Institution:School of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA;Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;Institute for Environmental Genomics, Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA;Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China;Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Abstract:The elemental sulfur (S0) recovery was evaluated in the presence of nitrate in two development models of simultaneous desulfurization and denitrification (SDD) process. At the loading rates of 0.9 kg S/(m3·day) for sulfide and 0.4 kg N/(m3·day) for nitrate, S0 conversion rate was 91.1% in denitrifying sulfide removal (DSR) model which was higher than in integrated simultaneous desulfurization and denitrification (ISDD)model (25.6%). A comprehensive analysis of functional diversity, structure and metabolic potential of microbial communities was examined in two models by using functional gene array (GeoChip 2.0). GeoChip data indicated that diversity indices, community structure, and abundance of functional genes were distinct between two models. Diversity indices (Simpson's diversity index (1/D) and Shannon-Weaver index (H')) of all detected genes showed that with elevated influent loading rate, the functional diversity decreased in ISDD model but increased in DSR model. In contrast to ISDD model, the overall abundance of dsr genes was lower in DSR model, while some functional genes targeting from nitrate-reducing sulfide-oxidizing bacteria (NR-SOB), such as Thiobacillus denitrificans, Sulfurimonas denitrificans, and Paracoccus pantotrophus were more abundant in DSR model which were highly associated with the change of S0 conversion rate obtained in twomodels. The results obtained in this study provide additional insights into themicrobialmetabolicmechanisms involved in ISDD and DSR models, which in turn will improve the overall performance of SDD process.
Keywords:Expanded granular sludge bed  Elemental sulfur recovery  Microbial community  Functional gene array
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