摘要
      抗生素耐药性是我们这个时代对全球人类和动物健康的最大威胁之一。城市污水已被确定为水体抗生素耐药性污染的热点。然而，有许多潜在的抗生素耐药性病原体及其相关的抗生素耐药性基因（ARGs），这使得很难实施常规监测来解决问题的广度。本研究的目的是确定用于监测废水和接收水体中抗生素耐药性的候选指标ARGs。我们开发了一个框架来识别指标ARG，该框架包括临床相关性、废水丰度、地理普遍性、环境相关性、ARG流动性、与流动遗传元素的关联以及定量分析方法的可用性。为了识别指标ARGs，从在线公共存储库中获得了来自全球64个国家的191个废水样本的已发表宏基因组测序数据。通过ARG注释和网络分析，该框架揭示了分布在四个强相关ARG模块中的56个候选指标ARG，每个模块（oqxA、ermB、sul1和mexE）中的一个ARG被建议作为最小冗余监测目标。本研究的结果为废水和受污染水道的抗生素耐药性监测和监测框架提供了基础。
Abstract
Antibiotic resistance is one of the greatest threats to global human and animal health of our time. Municipal wastewater has been identified as a hotspot of antibiotic resistance contamination to water bodies. However, there are numerous potential antibiotic resistant pathogens and their associated antibiotic resistance genes (ARGs), making it difficult to implement routine monitoring that addresses the breadth of the problem. The objective of this study was to identify candidate indicator ARGs for monitoring antibiotic resistance in wastewater and receiving water bodies. We developed a framework to identify indicator ARGs that incorporated clinical relevance, abundance in wastewater, geographic ubiquity, environmental relevance, ARG mobility, associations with mobile genetic elements, and the availability of quantitative analytical methods. To identify indicator ARGs, published metagenomic sequencing data from 191 wastewater samples originating from 64 countries across the world were obtained from online public repositories. Through ARG annotation and network analysis, this framework revealed 56 candidate indicator ARGs distributed across four modules of strongly correlated ARGs, with one ARG from each module (oqxA, ermB, sul1, and mexE) proposed as a minimally redundant monitoring target. The results of this study provide the basis for antibiotic resistance surveillance and monitoring framework in wastewater and contaminated waterways.

https://www.sciencedirect.com/science/article/abs/pii/S0048969722057977