摘要

      抗生素耐药性是一个日益受到关注的公共卫生问题，环境被认为是抗生素耐药基因（ARGs）的重要贮存和传播途径。正确理清环境中ARGs的源库关系，是防治ARG污染的关键。然而，由于环境中多种污染源和污染物在动态变化中的复杂相互作用，精确地分配ARGs的来源仍然是一个巨大的挑战。在这项研究中，我们解决了这个问题，并着重于通过联合使用两种新的微生物源追踪方法来识别城郊河流中ARGs的潜在来源。为了达到这一目的，我们从城郊河流和四种ARG相关生态类型（包括污水处理厂（STPs）的废水、STP进水、鸡粪和猪粪）中采集了沉积物/水样本。采用鸟枪测序和亚基因组组装分析相结合的方法，对河流沉积物和4种生态型的ARGs和微生物类群的高通量利润进行了综合表征。CrAssphage是最近发现的一种DNA噬菌体，用于跟踪人类粪便污染对河流沉积物中ARGs的影响。此外，SourceTracker是一种机器学习的分类工具，用于根据ARGs和微生物类群的亚基因组特征，量化潜在来源对河流沉积物中ARGs的贡献。在所有样本中，共检测到888个ARG亚型，隶属于29个ARG亚型，包括mcr-1和一系列碳青霉烯酶亚型。统计分析表明，不同生态型的ARGs和微生物类群的分布基本一致，而ARG的组成与微生物群落有显著的相关性。用crAssphage进行污染源跟踪表明，河流沉积物中ARGs的存在可能主要受人类粪便污染程度的影响，源跟踪分析也证实了STPs的排放是河流沉积物中ARGs（81.6-92.1%）和微生物（49.3-68.1%）的最大贡献者。研究结果有助于我们更好地了解城市周边生态系统中ARGs的特征，设计有效的防治策略，减少ARG的传播。

       Antimicrobial resistance is a growing public health concern, and environment is regarded as an important reservoir and dissemination route for antibiotic resistance genes (ARGs). To prevent and control ARG pollution, it is essential to correctly disentangle source-sink relationship of ARGs in the environment. However, accurately apportioning sources of ARGs is still a big challenge due to the complex interaction of multiple sources and contaminants in the environment with changing dynamics. In this study, we addressed this problem and focused on identifying the potential sources of ARGs in a peri-urban river by jointly utilizing two novel microbial source tracking methods. To attain the objective, sediment/water samples were collected from the peri-urban river and four ARG-associated ecotypes including effluents of sewage treatment plants (STPs), STP influent, chicken manures and pig manures. The high-throughput profilings of ARGs and microbial taxa in the river sediments and the four ecotypes were comprehensively characterized in combination of shotgun sequencing and metagenomic assembly analysis. CrAssphage, a recently-discovered DNA bacteriophage, was employed to track the impact of human fecal pollution on ARGs in the river sediments. Further, SourceTracker, a machine-learning classification tool, was used for quantifying the contributions of potential sources to ARGs in the river sediments based on the metagenomic signatures of ARGs and microbial taxa. In total, 888 ARG subtypes belonging to 29 ARG types were detected across all samples, including mcr-1 and a range of carbapenemases types. Statistical analyses suggested different ecotypes generally had distinct profiles of both ARGs and microbial taxa, while the ARG compositions were significantly correlated with the microbial community. Source tracking with crAssphage showed the presence of ARGs in the river sediments might be largely impacted by the extent of human fecal pollution, which was also confirmed by the analyses of SourceTracker that the discharge from STPs was the largest contributor of ARGs (81.6-92.1%) and microbes (49.3-68.1%) in the river sediments. Results of the study can help us to better understand the characterization of ARGs in the peri-urban ecosystem and to design effective prevention and control strategies for reducing ARG dissemination.

       https://linkinghub.elsevier.com/retrieve/pii/S0043-1354(19)30872-3