摘要
      环境是抗微生物耐药性（AMR）出现和传播的重要组成部分。尽管如此，目前的AMR监测举措缺乏针对绝大多数环境的全面参考数据。为了能够进行监测以检测环境中与正常背景电阻水平的偏差，有必要在各种设置中建立AMR的典型基线。为了建立这一基线水平，我们在这里对2516篇科学论文进行了全面的文献调查，其中150篇包含了与AMR潜在传播途径相关的环境中抗生素耐药性基因（ARGs）的相关qPCR数据。收集的数据包括2005年至2018年期间分布在30个不同国家和17种环境类型的1487个样本。从收集的研究中鉴定出330多个不同的基因。大多数被调查的环境都包含一组不同的ARG，但通常丰度较低。我们使用线性混合模型和过度代表性分析来确定ARG与特定环境之间的时间趋势和关联。总之，这些数据全面概述了不同环境中ARG的发生和水平，为当前和未来AMR监测框架内的风险评估模型提供了背景数据。
Abstract
The environment is an important component in the emergence and transmission of antimicrobial resistance (AMR). Despite that, current AMR monitoring initiatives lack comprehensive reference data for the vast majority of environments. To enable monitoring to detect deviations from the normal background resistance levels in the environment, it is necessary to establish the typical baseline of AMR in a variety of settings. In an attempt to establish this baseline level, we here performed a comprehensive literature survey across 2516 scientific papers, 150 of which contained relevant qPCR data on antibiotic resistance genes (ARGs) in environments associated with potential routes of AMR dissemination. The collected data include 1487 samples distributed across 30 different countries and 17 environmental types, in a time span from 2005 to 2018. More than 330 different genes were identified from the collected studies. Most surveyed environments contained a diverse set of ARGs, but generally at low abundances. We used linear mixed models and overrepresentation analysis to identify time trends and associations between ARGs and specific environments. Altogether these data represent a comprehensive overview of the occurrence and levels of ARGs in different environments, providing background data for risk assessment models within current and future AMR monitoring frameworks.

https://www.biorxiv.org/content/10.1101/2022.01.29.478248v1.abstract