Abstract：
Although the presence of antibiotic resistance genes (ARGs) in drinking water and their potential horizontal gene transfer to pathogenic microbes are known to pose a threat to human health, their pollution levels and potential anthropogenic sources are poorly understood. In this study, broad-spectrum ARG profiling combined with machine-learning-based source classification SourceTracker was performed to investigate the pollution sources of ARGs in household drinking water collected from 95 households in 47 cities of eight countries/regions. In total, 451 ARG subtypes belonging to 19 ARG types were detected with total abundance in individual samples ranging from 1.4 × 10-4 to 1.5 × 10° copies per cell. Source tracking analysis revealed that many ARGs were highly contributed by anthropogenic sources (37.1%), mainly wastewater treatment plants. The regions with the highest detected ARG contribution from wastewater (∼84.3%) used recycled water as drinking water, indicating the need for better ARG control strategies to ensure safe water quality in these regions. Among ARG types, sulfonamide, rifamycin and tetracycline resistance genes were mostly anthropogenic in origin. The contributions of anthropogenic sources to the 20 core ARGs detected in all of the studied countries/regions varied from 36.6% to 84.1%. Moreover, the anthropogenic contribution of 17 potential mobile ARGs identified in drinking water was significantly higher than other ARGs, and metagenomic assembly revealed that these mobile ARGs were carried by diverse potential pathogens. These results indicate that human activities have exacerbated the constant input and transmission of ARGs in drinking water. Our further risk classification framework revealed three ARGs (sul1, sul2 and aadA) that pose the highest risk to public health given their high prevalence, anthropogenic sources and mobility, facilitating accurate monitoring and control of anthropogenic pollution in drinking water.
摘要：
尽管已知饮用水中抗生素抗性基因（ARGs）的存在及其潜在的对病原微生物的水平基因转移对人类健康构成威胁，他们的污染水平和潜在的人为来源知之甚少。在这项研究中,进行了广谱ARG分析与基于机器学习的源分类相结合的SourceTracker，以调查从8个国家/地区的47个城市的95个家庭收集的家庭饮用水中ARG的污染源。总的来说,检测到属于19种ARG类型的451种ARG亚型，单个样品中的总丰度范围为每个细胞1.4×10-4至1.5×10°拷贝。来源追踪分析表明，许多ARGs是由人为来源贡献的(37.1%)，主要是污水处理厂。废水中检测到的ARG贡献最高的地区(~84.3%)使用循环水作为饮用水，表明需要更好的ARG控制策略，以确保这些地区的安全水质。在ARG类型中，磺酰胺,利福霉素和四环素抗性基因大多是人为起源的。在所有研究的国家/地区中，人为来源对20种核心ARG的贡献从36.6％到84.1％不等。此外，在饮用水中发现的17种潜在移动ARGs的人为贡献明显高于其他ARGs，宏基因组组装表明，这些移动ARG由多种潜在病原体携带。这些结果表明，人类活动加剧了饮用水中ARGs的不断输入和传播。我们进一步的风险分类框架揭示了三种ARG(sul1、sul2和aadA)，鉴于其高流行率，它们对公共卫生构成最高风险，人为来源和流动性，促进准确监测和控制饮用水中的人为污染。
