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抗生素耐药组在大范围地理区域的饮用水源中的分布:多种驱动因素以及与机会性细菌病原体的共存。

Antibiotic resistomes in drinking water sources across a large geographical scale: Multiple drivers and co-occurrence with opportunistic bacterial pathogens.

机构信息

State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.

State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.

出版信息

Water Res. 2020 Sep 15;183:116088. doi: 10.1016/j.watres.2020.116088. Epub 2020 Jun 22.

Abstract

Antibiotic resistance genes (ARGs) can survive the water treatment process. However, the prevalence patterns, key drivers, and relationships with opportunistic pathogens of the antibiotic resistome harbored in drinking water sources remain unclear. Herein, 53 drinking water samples collected across a large geographical scale in China were characterized based on ARGs, mobile genetic elements (MGEs), bacterial communities, antibiotics, and opportunistic bacterial pathogens. A total of 265 unique ARGs and MGEs were detected by high-throughput quantitative polymerase chain reaction (HT-qPCR), and 101 genes were shared among over 50% of samples. ARG abundance was higher in rivers than in reservoirs or groundwater, and ARG similarity showed a distance-decay relationship at the >4 000 km scale. Four out of the five detected opportunistic pathogens (i.e., Escherichia coli, Mycobacterium spp., Clostridium perfringens, and Bacillus cereus group) were potential hosts of ARGs. Based on multivariate statistics, our results demonstrated that the factors influencing the antibiotic resistome in drinking water sources were multiple and interactive. The bacterial community greatly contributed to ARG structure, and antibiotic concentrations and MGEs also affected ARG proliferation. The structural equation model indicated that geographical location and sample types (i.e., river, reservoir, and groundwater) had indirect effects on ARGs by changing the bacterial community and antibiotic concentration. Holistic consideration of natural and anthropogenic factors is recommended to understand antibiotic resistome variation in drinking water sources at a large geographical scale. Furthermore, large-scale diverse samples are suggested to minimize the potential influence of accident or stochasticity. Our findings provide insight into water quality risks induced by drinking water antibiotic resistomes.

摘要

抗生素耐药基因 (ARGs) 能够在水处理过程中存活下来。然而,饮用水源中抗生素耐药组中抗生素耐药基因的流行模式、关键驱动因素和与机会性病原体的关系尚不清楚。在此,我们对中国大范围内采集的 53 个饮用水样本进行了基于 ARGs、移动遗传元件 (MGEs)、细菌群落、抗生素和机会性病原体的特征描述。通过高通量定量聚合酶链反应 (HT-qPCR) 共检测到 265 个独特的 ARGs 和 MGEs,其中 101 个基因在超过 50%的样本中共享。河流中的 ARG 丰度高于水库或地下水,而 ARG 相似性在>4000km 的尺度上呈距离衰减关系。在检测到的五种机会性病原体(即大肠杆菌、分枝杆菌、梭状芽孢杆菌和芽孢杆菌群)中,有四种是 ARG 的潜在宿主。基于多元统计分析,我们的结果表明,影响饮用水源抗生素耐药组的因素是多方面的、相互作用的。细菌群落对 ARG 结构有很大的贡献,抗生素浓度和 MGEs 也影响 ARG 的增殖。结构方程模型表明,地理位置和样本类型(即河流、水库和地下水)通过改变细菌群落和抗生素浓度对 ARGs 产生间接影响。建议综合考虑自然和人为因素,以了解大地理范围内饮用水源中抗生素耐药组的变化。此外,建议使用大规模的多样化样本,以最小化偶然或随机性的潜在影响。我们的研究结果为了解饮用水抗生素耐药组引起的水质风险提供了新的视角。

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