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Response of microbial communities of karst river water to antibiotics and microbial source tracking for antibiotics
被引:42
作者:
Xiang, Shizheng
[1
]
Wang, Xusheng
[1
]
Ma, Wen
[1
]
Liu, Xiaoping
[1
]
Zhang, Biao
[1
]
Huang, Fuyang
[2
]
Liu, Fei
[2
]
Guan, Xiangyu
[1
,2
]
机构:
[1] China Univ Geosci Beijing, Sch Ocean Sci, Beijing 100083, Peoples R China
[2] China Univ Geosci Beijing, Beijing Key Lab Water Resources & Environm Engn, Beijing 100083, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Antibiotics;
Co-occurrence networks;
Ecological cluster;
Karst river water;
Microbial source tracking;
RESISTANCE GENES;
BACTERIAL COMMUNITY;
WASTE-WATER;
SYSTEM;
CHINA;
GROUNDWATER;
CONTAMINATION;
PREVALENCE;
DIVERSITY;
NORTHERN;
D O I:
10.1016/j.scitotenv.2019.135730
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
In southwestern China, karst river water is the main source of water for humans. As emerging pollutants, antibiotics have contaminated karst river water in some areas for a long time. Microbiota is highly susceptible to environmental changes, and can be used in tracing the source of antibiotics in complex systems such as karst water. Ten karst river water samples were collected along the river flow. The diversity and structure of the microbial community were analyzed together with environmental factors through correlation analysis, the random forest algorithm and co-occurence network analysis. At genus level, Arcobacler was significantly positively correlated with the antibiotics, indicating that Arcobacler and antibiotics probably came from the same source. Based on co-occurrence network analysis between microbes, the microbial community was divided into eight modules, and the relative abundance of three modules was significantly correlated with antibiotics. The co-occurrence networks between bacteria and antibiotic resistance genes (ARGs) showed that pathogenic bacteria potentially carried multiple ARGs. This could increase the disease risk to humans and disease transmission in the study area. When river water flowed underground, the concentration of antibiotics decreased for the two underground river outlet sites, but abundance of bacteria and ARGs increased. Microbial source tracking studies showed that contamination was derived from humans rather than livestock. The ranking importance of prediction for antibiotics in this study area from random forest follows: specific bacteria Arcobacter > ARGs > ecological clusters. This study will be helpful in identifying the effect of antibiotics discharge on the microbial community, improving evaluation of antibiotics' risks and contaminants source tracking. (C) 2019 Elsevier B.V. All rights reserved.
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页数:8
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