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Microbial community structure in a channel catfish pond in Nanjing, China
Received:February 16, 2020  
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KeyWord:channel catfish;pond;water body;microbial community;high-throughput sequencing technique
Author NameAffiliationE-mail
ZHONG Li-qiang Freshwater Fisheries Research Institute of Jiangsu Province, Nanjing 210017, China
Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
University of Chinese Academy of Sciences, Beijing 100049, China 
 
WANG Ming-hua Freshwater Fisheries Research Institute of Jiangsu Province, Nanjing 210017, China  
ZHANG Shi-yong Freshwater Fisheries Research Institute of Jiangsu Province, Nanjing 210017, China  
JIANG Hu-cheng Freshwater Fisheries Research Institute of Jiangsu Province, Nanjing 210017, China  
CHEN Xiao-hui Freshwater Fisheries Research Institute of Jiangsu Province, Nanjing 210017, China  
ZHU Guang-wei Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China gwzhu@niglas.ac.cn 
BIAN Wen-ji Freshwater Fisheries Research Institute of Jiangsu Province, Nanjing 210017, China js6060@sina.com 
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Abstract:
      Microbes play important roles in aquaculture environments. Consequently, to understand and predict the response of such an ecosystem to environmental changes, there is an urgent need to explore the structure and constructive mechanism of microbial communities in aquaculture ponds. This study characterized the structure of microbial communities in water samples from a channel catfish pond in Nanjing, China. High-throughput sequencing of the V3-V4 hypervariable region in the 16S rRNA gene was used to investigate the microbiome structural characters. The results showed that the bacterial community structure exhibited a strong seasonal change, whereby a distinct temporal succession was evident over the entire year. The bacterial community compositions were similar between the winter and spring and between the summer and autumn. The dominant phyla in water samples were Cyanobacteria, Actinobacteria, Proteobacteria, and Bacteroidetes. Among the measured environmental variables, TDS, temperature, pH, NO2--N, and TOC were observed as the primary drivers for the bacterial communities (r2>0.6), which also had a significant correlation with the bacterial community structure(P<0.05).