摘要

       抗生素抗性基因 (ARG) 的传播是一个日益严重的全球性问题。污水处理厂 (WWTP) 中的活性污泥 (AS) 已被提议作为 ARG 的热点。然而，很少有研究通过长期纵向采样来揭示污水处理厂中 AS 抗性组的时间动态。在这项研究中，我们在 9 年的 97 个每月 AS 样本中量化了 ARGs 并确定了它们在香港污水处理厂的宿主微生物组。在整个分析过程中，我们证明了抗性组的丰度和结构每两到三年都会发生显着变化，这意味着在研究期间 AS 系统中存在连续的抗性组选择。在 AS 样本中检测对公共健康构成重大威胁的抗生素耐药病原体的基因，包括 mcr、CRE（耐碳青霉烯肠杆菌科）和 MRSA（耐甲氧西林金黄色葡萄球菌）相关基因，突出了污水处理厂的作用作为 ARG 的储存库。此外，发现 AS 中的核心抗性组（丰富且持久的基因）与其他生态系统中的抗性组（如城市污水、牲畜粪便和鱼塘沉积物）重叠，揭示了 ARGs 在污水处理厂和其他环境中的广泛传播。通过结构方程模型 (SEM) 解释了抗性组的年度变化，该模型破译了诸如操作参数、微生物群落组成和水平基因转移 (HGT) 等决定因素的结构联系。具体而言，基于基于组装的分析和网络相关性，探索和讨论了潜在相关的抗生素抗性细菌 (ARB)。此外，与抗性组和移动遗传元件（MGEs）之间的明确关系一致，发现与土壤基因组相比，AS 中基因交换的潜力相对较高，这可以通过污水处理厂的工程特征来解释。基于这些发现，有必要对污水处理厂进行纵向监测，以进行风险评估，以揭示新出现的 ARG、抗性进化、与 ARB 的相关性，以及在下游环境中传播的可能性以及伴随的人类暴露风险。

       The spread of antibiotic resistance genes (ARGs) is a growing global problem. Activated sludge (AS) in wastewater treatment plants (WWTPs) has been proposed as a hotspot for ARGs. However, few studies have been conducted to uncover the temporal dynamics of the resistome of AS in WWTPs by long-term longitudinal sampling. In this study, we quantified ARGs and identified their host microbiome in a Hong Kong WWTP in 97 monthly AS samples spanning 9 years. Throughout this analysis, we demonstrated that both the abundance and structures of the resistome changed significantly every two to three years, implying that there was a successive selection of resistomes in the AS system over the study period. The detection of genes of antibiotic-resistant pathogens that are emerging major threats to public health in the AS samples, including mcr, CRE (carbapenem-resistant Enterobacteriaceae) and MRSA (methicillin-resistant Staphylococcus aureus)-related genes, highlight the role of WWTPs as reservoirs of ARGs. In addition, the core resistome (abundant and persistent genes) in AS were found to overlap with those in other ecosystems such as urban sewage, livestock feces, and fishpond sediments, revealing the broad dissemination of ARGs in WWTPs and other environments. Annual variation of resistomes were explained via structural equation modeling (SEM), which deciphered the structural linkages of determining factors such as the operational parameters, microbial community composition and horizontal gene transfer (HGT). Specifically, potentially relevant antibiotic resistance bacteria (ARBs) were explored and discussed based on assembly-based analyses and network correlations. Moreover, consistent with the clear relationship between resistomes and mobile genetic elements (MGEs), it was found that there was a relatively high potential for gene exchange in AS in comparison with soil genomes, which could be explained by the engineering features of WWTPs. Based on these findings, longitudinal monitoring of WWTPs is warranted for risk assessment to reveal emerging ARGs, resistome evolution, correlations with ARBs, and the potential for spread in downstream environments and concomitant exposure risks for humans.
https://www.sciencedirect.com/science/article/pii/S0160412019321774