摘要
      基于污水的监测被广泛用于了解城市社区抗微生物耐药性（AMR）的发生和分布。然而，对社区内不同来源的污水进行调查的研究有限。本研究使用宏基因组学来破译五个来源的AMR谱：当地居民来源、动物来源、农民工来源、临床来源和城市污水处理厂进水。在所有样本中都发现了ARGs的核心抗性，占总抗性丰度的81.4%-9.3%，仅17.3%的多样性，无论污水来源如何。在所有废水来源的核心耐药性中发现了临床相关的ARG。其中包括对β-内酰胺类抗生素产生耐药性的基因，作为医院污水的生物标志物。宠物中心的废水显示出大量编码四环素耐药性的基因，四环素是一种常用的兽医抗生素。外来务工人员宿舍污水的耐药谱与当地居民的耐药谱略有差异，这表明外国/外来务工人员的人类肠道耐药谱可能存在差异，编码磷霉素、磷米霉素、卡苏加霉素、MLS和多粘菌素耐药基因的生物标志物。ARGs和质粒、MGE以及整合和偶联元件（ICEs）的共同定位可以解释核心耐药组的变化，这可能是高抗生素选择压力的结果。进一步的分析显示了一种特定的宿主相关抗性模式，其中核心宿主介导了核心抗性谱。核心BMRGs也与MGEs/ICE共同定位，并由核心潜在细菌宿主携带。当地健康人群的ARG负荷最低（每人每天出院的拷贝数），但ARG负荷最高（人群出院的拷贝数量）。这项研究阐明了核心耐药组基于人群的变异，并进一步为城市环境中AMR的来源跟踪和管理提供了重要见解。
Abstract
Sewage-based surveillance is widely employed to understand the occurrence and distribution of antimicrobial resistance (AMR) in urban community. However, there are limited studies which investigated the sewage of different sources within community. The present study used metagenomics to decipher the AMR profiles in five sources: local residence’s source, animal source, migrant workers’ source, clinical source , and urban wastewater treatment plant influent. A core resistome of ARGs was found across all samples, accounting for 81.4%-93.3% of the abundance of total resistome with only 17.3% diversity, irrespective of the sewage sources. Clinically relevant ARGs were identified in the core resistome across all wastewater sources. This included genes conferring resistance to beta-lactams as biomarkers of hospital sewage. The pet center wastewater showed a high abundance of genes encoding resistance to tetracycline, which is a commonly used veterinary antibiotic. The resistome profile of sewage from the migrant workers’ dormitories showed a slight variation to that of the local residential population, suggesting possible differences in the human gut resistome of the foreign/migrant population, with biomarkers of genes encoding resistance to fosfomycin, fosmidomycin, kasugamycin, MLS, and polymyxin. The co-localization of ARGs and plasmid, MGEs and integrative and conjugative elements (ICEs) could explain variations in the core resistome, presumably a result of high antibiotic selection pressure. Further analysis showed a specific host-associated resistance pattern, in which core hosts mediated the core resistome profile. The core BMRGs were also co-localized with MGEs/ICEs and carried by core potential bacterial hosts. Local healthy population carried the lowest ARG load (copy number discharged by each person per day) but contributed the highest ARG burden (copy number discharged by the population). This study elucidates population-based variations of a core resistome, and further provides important insights into source tracking and management of AMR in urban environments.

https://www.sciencedirect.com/science/article/pii/S0160412022001118