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环境中抗生素抗性基因丰度与抗生素和重金属含量的相关性分析:基于Web of Science数据库检索
摘要点击 2490  全文点击 851  投稿时间:2021-01-06  修订日期:2021-03-18
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中文关键词  抗生素抗性基因(ARGs)  抗生素  重金属  相关分析  文献检索
英文关键词  antibiotic resistance genes(ARGs)  antibiotics  heavy metals  correlation analysis  literature search
作者单位E-mail
苗荪 清华大学环境学院, 环境模拟与污染控制国家重点联合实验室, 北京 100084 miaos20@mails.tsinghua.edu.cn 
陈磊 清华大学环境学院, 环境模拟与污染控制国家重点联合实验室, 北京 100084  
左剑恶 清华大学环境学院, 环境模拟与污染控制国家重点联合实验室, 北京 100084 jiane.zuo@mail.tsinghua.edu.cn 
中文摘要
      抗生素和重金属是两种重要的环境污染物和耐药性选择压力源,但低含量水平下其对环境微生物种群耐药性水平的影响尚不明确.本文全面检索了截至2020年1月1日发表在Web of Science数据库中同时监测了抗生素抗性基因(ARGs)丰度、抗生素含量或重金属含量的研究文献,提取相关数据,利用统计回归方法调查环境介质中3个参数的相关关系.结果表明,除废水外,地表水、沉积物和土壤等环境介质中,即使在非常低的抗生素含量水平下,抗生素选择压力也会对ARGs丰度的增加产生显著的统计效应(P<0.05).不同类别抗生素对耐药基因表现出不同程度的选择和富集作用.重金属含量以及抗生素含量和重金属含量的交互作用对ARGs的传播也具有显著影响(P<0.05).水相和固相环境样本的多变量统计回归模型的最终R2分别为0.482和0.707,比单变量回归的R2更高,能更好地解释ARGs丰度的差异,但环境中还存在其他可能影响ARGs丰度的因素.本文的研究结果可为环境中抗生素耐药性风险评估及传播控制提供支撑.
英文摘要
      Antibiotics and heavy metals are both important environmental pollutants and selective stressors for antibiotic resistance. However, the impact of their environmental concentrations on antibiotic resistance levels is still unclear. In this paper, research published before 2019 reporting the abundance of antibiotic resistance genes(ARGs), antibiotics concentrations, or heavy metal concentrations were extracted from the Web of Science database, and then statistical regression was used to investigate their correlative association. The results show that antibiotic selection pressure has a statistically significant effect on the increase in the abundance of ARGs in environmental media such as surface water, sediment, and soil, even at very low antibiotic concentrations(P<0.05). Different classes of antibiotics show different potential to select and enrich ARGs. Heavy metals and the interaction between antibiotics and heavy metals also have significant effects on ARG transmission(P<0.05). Multivariate statistical regression models can better explain the variance of ARG abundance, with R2 values for the water phase and solid phase environmental samples of 0.482 and 0.707 respectively, which are much higher than those achieved using univariate regression models. However, additional environmental factors not included may also affect ARG abundance. The results of this work provide a basis for the evaluation and control of environmental antibiotic resistance.

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