Ahmed Warish, Gyawali Pradip, Hamilton Kerry A, Joshi Sayalee, Aster David, Donner Erica, Simpson Stuart L, Symonds Erin M
CSIRO Land and Water, Ecosciences Precinct, Dutton Park, QLD, Australia.
Institute of Environmental Science and Research Ltd. (ESR), Porirua, New Zealand.
Front Microbiol. 2021 Jun 11;12:632850. doi: 10.3389/fmicb.2021.632850. eCollection 2021.
Since sewage is a hotspot for antibiotic resistance genes (ARGs), the identification of ARGs in environmental waters impacted by sewage, and their correlation to fecal indicators, is necessary to implement management strategies. In this study, sewage treatment plant (STP) influent samples were collected and analyzed using quantitative polymerase chain reaction (qPCR) to investigate the abundance and correlations between sewage-associated markers (i.e., HF183, Lachno3, crAssphage) and ARGs indicating resistance to nine antibiotics (belonging to aminoglycosides, beta-lactams, sulfonamides, macrolides, and tetracyclines). All ARGs, except , and sewage-associated marker genes were always detected in untreated sewage, and and were detected in the greatest abundances. was also highly abundant in untreated sewage samples. Significant correlations were identified between sewage-associated marker genes, ARGs and the in untreated sewage (τ = 0.488, = 0.0125). Of the three sewage-associated marker genes, the BIO-ENV procedure identified that HF183 alone best maximized correlations to ARGs and (τ = 0.590). Additionally, grab samples were collected from peri-urban and urban sites along the Brisbane River system during base and stormflow conditions, and analyzed for , ARGs, the , and sewage-associated marker genes using quantitative polymerase chain reaction (qPCR). Significant correlations were identified between , ARGs, and (τ = 0.0893, = 0.0032), as well as with sewage-associated marker genes in water samples from the Brisbane River system (τ = 0.3229, = 0.0001). Of the sewage-associated marker genes and , the BIO-ENV procedure identified that crAssphage alone maximized correlations with ARGs and in river samples (τ = 0.4148). Significant differences in , ARGs, , and sewage-associated marker genes, and by flow condition (i.e., base vs. storm), and site types (peri-urban vs. urban) combined were identified ( = 0.3668, = 0.0001), where percent dissimilarities between the multi-factorial groups ranged between 20.8 and 11.2%. Results from this study suggest increased levels of certain ARGs and sewage-associated marker genes in stormflow river water samples compared to base flow conditions. , HF183 and crAssphage may serve as potential indicators of sewage-derived ARGs under stormflow conditions, and this merits further investigation. Data presented in this study will be valuable to water quality managers to understand the links between sewage pollution and ARGs in urban environments.
由于污水是抗生素抗性基因(ARGs)的一个热点,因此识别受污水影响的环境水体中的ARGs及其与粪便指示物的相关性,对于实施管理策略是必要的。在本研究中,收集了污水处理厂(STP)进水样本,并使用定量聚合酶链反应(qPCR)进行分析,以研究污水相关标志物(即HF183、Lachno3、crAssphage)与指示对九种抗生素(属于氨基糖苷类、β-内酰胺类、磺胺类、大环内酯类和四环素类)耐药性的ARGs之间的丰度及相关性。除了[此处原文缺失具体基因名称]外,所有ARGs以及污水相关标志物基因在未经处理的污水中均能检测到,且[此处原文缺失具体基因名称]和[此处原文缺失具体基因名称]的检测丰度最高。[此处原文缺失具体基因名称]在未经处理的污水样本中也高度丰富。在未经处理的污水中,污水相关标志物基因、ARGs与[此处原文缺失具体指标名称]之间存在显著相关性(τ = 0.488,P = 0.0125)。在这三种污水相关标志物基因中,BIO-ENV程序确定仅HF183与ARGs和[此处原文缺失具体指标名称]的相关性最佳(τ = 0.590)。此外,在基流和暴雨径流条件下,从布里斯班河系的城郊和城市地点采集了抓取样本,并使用定量聚合酶链反应(qPCR)分析了[此处原文缺失具体指标名称]、ARGs、[此处原文缺失具体指标名称]以及污水相关标志物基因。在[此处原文缺失具体指标名称]、ARGs和[此处原文缺失具体指标名称]之间存在显著相关性(τ = 0.0893,P = 0.0032),并且与布里斯班河系水样中的污水相关标志物基因也存在显著相关性(τ = 0.3229,P = 0.0001)。在污水相关标志物基因[此处原文缺失具体基因名称]和[此处原文缺失具体基因名称]中,BIO-ENV程序确定仅crAssphage与河流样本中的ARGs和[此处原文缺失具体指标名称]的相关性最佳(τ = 0.4148)。确定了[此处原文缺失具体指标名称]、ARGs、[此处原文缺失具体指标名称]以及污水相关标志物基因在流量条件(即基流与暴雨径流)和地点类型(城郊与城市)组合方面存在显著差异(P = .3668,P = 0.0001),其中多因素组之间的差异百分比在20.8%至11.2%之间。本研究结果表明,与基流条件相比,暴雨径流水样中某些ARGs和污水相关标志物基因的水平有所升高。[此处原文缺失具体指标名称]、HF183和crAssphage可能是暴雨径流条件下污水来源ARGs的潜在指示物,这值得进一步研究。本研究提供的数据对于水质管理人员了解城市环境中污水污染与ARGs之间的联系将具有重要价值。