摘要
      污水处理厂（eSTP）的废水是河流中抗生素耐药性的重要贡献者之一。最近，随着整个微生物组相互交换，群落聚结成为人们关注的焦点。虽然有工作报道了eSTP中抗生素耐药性基因（ARGs）的流行及其对河流耐药性的影响，但很少有研究调查环境中耐药性合并的程度。在这项研究中，我们解决了这个问题，并通过利用基于高通量测序（HTS）的宏基因组组装分析，利用典型的污水/河流聚结模型，重点研究了城市河流中eSTP的抗性聚结。总的来说，在eSTP河流系统中共发现609个ARG，对30种抗生素产生耐药性，其中包括一些新出现的ARG，如mcr型、tetX和碳青霉烯酶基因。包括线性判别分析效应大小（LEfSe）在内的统计分析表明，污水处理厂废水的聚结增加了河流抗性组的多样性和丰度，表明其对eSTP中抗性组群落入侵的抵抗力较低。在河流中汇合后，STP衍生的ARGs的印记沿着流动路径呈现暂时增加和逐渐减少的趋势。此外，创新的快速期望最大化微生物源跟踪（FEAST）方法被用于定量分配聚结事件，并证明了eSTP对河流阻力的贡献及其在下游的衰减动力学。值得注意的是，基于相关性的网络分析和基于重叠群的共现分析表明，下游河流中的联合耐药组与人类细菌病原体、可移动遗传元件和毒力因子基因共同发生，表明潜在的耐药组在环境中传播风险。这项研究对工程环境和自然环境之间的抗性结合有了更深刻的理解，有助于优化预防和控制水生环境中抗性风险的策略。
Abstract
The effluents of sewage treatment plants (eSTP) are one of the critical contributors of antibiotic resistiome in rivers. Recently, community coalescence has been focused as the entire microbiome interchanges with one another. While works have reported the prevalence of antibiotic resistance genes (ARGs) in eSTP and their effects on river resistome, little research has investigated the extent of resistome coalescence in the environment. In the study, we have addressed the issue and focused on the resistome coalescence of eSTP in an urban river with a typical effluent/river coalescence model, by utilizing high-throughput sequencing (HTS)-based metagenomic assembly analysis. In all, a total of 609 ARGs were found in the eSTP-river system, conferring resistance to 30 antibiotic classes and including some emerging ARGs such as mcr-type, tetX and carbapenemase genes. Statistical analyses including linear discriminant analysis effect size (LEfSe) showed the coalescence of STP effluents increased the diversity and abundance of river resistome, indicating its low resistance to disturb the invasion of resistome community in eSTP. After coalescence in the river, the imprints of STP-derived ARGs presented a temporary increase and gradually decreased trend along the flow path. Further, an innovative fast expectation-maximization microbial source tracking (FEAST) method was used to quantitatively apportion the coalescence event, and demonstrated the contribution of eSTP on river resistome and its attenuation dynamics in the downstream. Notably, correlation-based network analysis and contig-based co-occurrence analysis showed the coalesced resistome in the downstream river co-occurred with human bacterial pathogens, mobile genetic elements and virulence factor genes, indicating potential resistome dissemination risk in the environment. This study provides more profound understanding of resistome coalescence between engineered and natural contexts, which is helpful for optimizing strategies to prevent and control resistome risk in aquatic environment.

https://www.sciencedirect.com/science/article/abs/pii/S0043135422010077