Effects of graphite and Mn ore media on electro-active bacteria enrichment and fate of antibiotic and corresponding resistance gene in up flow microbial fuel cell constructed wetland

微生物燃料电池 微生物种群生物学 环境化学 化学 微生物学 地杆菌 细菌 生物 阳极 电极 生物膜 遗传学 物理化学
作者
Hua Li,Han Xu,Yu-Li Yang,Xiao-Li Yang,You Wu,Shuai Zhang,Hai–Liang Song
出处
期刊:Water Research [Elsevier BV]
卷期号:165: 114988-114988 被引量:129
标识
DOI:10.1016/j.watres.2019.114988
摘要

This study assessed the influence of substrate type on pollutants removal, antibiotic resistance gene (ARG) fate and bacterial community evolution in up-flow microbial fuel cell constructed wetlands (UCW-MFC) with graphite and Mn ore electrode substrates. Better COD removal and higher bacterial community diversity and electricity generation performance were achieved in Mn ore constructed UCW-MFC (Mn). However, the lower concentration of sulfadiazine (SDZ) and the total abundances of ARGs were obtained in the effluent in the graphite constructed UCW-MFC (s), which may be related to higher graphite adsorption and filter capacity. Notably, both reactors can remove more than 97.8% of ciprofloxacin. In addition, significant negative correlations were observed between SDZ, COD concentration, ARG abundances and bacterial a-diversity indices. The LEfse analysis revealed significantly different bacterial communities due to the substrate differences in the two reactors, and Geobacter, a typical model electro-active bacteria (EAB), was greatly enriched on the anode of UCW-MFC (Mn). In contrast, the relative abundance of methanogens (Methanosaeta) was inhibited. PICRUSt analysis results further demonstrated that the abundance of extracellular electron transfer related functional genes was increased, but the methanogen function genes and multiple antibiotic resistance genes in UCW-MFC (Mn) anode were reduced. Redundancy analyses indicated that substrate type, antibiotic accumulation and bacterial community were the main factors affecting ARGs. Moreover, the potential ARG hosts and the co-occurrence of ARGs and intI1 were revealed by network analysis.
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