Institute of Hydrobiology, Technische Universität Dresden, Dresden 01062, Zellescher Weg 40, Germany.
Department of Civil Engineering, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India.
FEMS Microbiol Ecol. 2023 Mar 23;99(4). doi: 10.1093/femsec/fiad031.
There is a clear need for global monitoring initiatives to evaluate the risks of antibiotic resistance genes (ARGs) towards human health. Therefore, not only ARG abundances within a given environment, but also their potential mobility, hence their ability to spread to human pathogenic bacteria needs to be quantified. We developed a novel, sequencing-independent method for assessing the linkage of an ARG to a mobile genetic element by statistical analysis of multiplexed droplet digital PCR (ddPCR) carried out on environmental DNA sheared into defined, short fragments. This allows quantifying the physical linkage between specific ARGs and mobile genetic elements, here demonstrated for the sulfonamide ARG sul1 and the Class 1 integron integrase gene intI1. The method's efficiency is demonstrated using mixtures of model DNA fragments with either linked and unlinked target genes: Linkage of the two target genes can be accurately quantified based on high correlation coefficients between observed and expected values (R2) as well as low mean absolute errors (MAE) for both target genes, sul1 (R2 = 0.9997, MAE = 0.71%, n = 24) and intI1 (R2 = 0.9991, MAE = 1.14%, n = 24). Furthermore, we demonstrate that adjusting the fragmentation length of DNA during shearing allows controlling rates of false positives and false negative detection of linkage. The presented method allows rapidly obtaining reliable results in a labor- and cost-efficient manner.
全球监测计划迫切需要评估抗生素耐药基因（ARGs）对人类健康的风险。因此，不仅需要评估特定环境中 ARG 的丰度，还需要评估其潜在的可移动性，即它们传播到人类致病菌的能力。我们开发了一种新的、与测序无关的方法，通过对环境 DNA 进行多重数字 PCR（ddPCR）分析，对特定 ARG 与移动遗传元件之间的连接进行统计评估，该方法对环境 DNA 进行了特定的短片段化处理。该方法可以定量特定 ARG 与移动遗传元件之间的物理连接，这里以磺胺类抗生素耐药基因 sul1 和整合子类 1 整合酶基因 intI1 为例进行了演示。该方法的效率通过使用带有连接和非连接靶基因的模型 DNA 片段混合物进行了验证：基于观察值与预期值之间的高相关系数（R2）和两个靶基因 sul1（R2 = 0.9997，MAE = 0.71%，n = 24）和 intI1（R2 = 0.9991，MAE = 1.14%，n = 24）的低平均绝对误差（MAE），可以准确地量化两个靶基因之间的连接。此外，我们还证明，通过调整 DNA 片段化长度，可以控制连接的假阳性和假阴性检测率。该方法可以快速、可靠地以低劳动和低成本的方式获得结果。
