摘要
      城市化海滩经常受到粪便污染的影响，但由于标准粪便指示菌（FIB）分析无法区分粪便物质的来源或检测其他微生物危害，包括抗生素耐药性基因（ARGs），解决污染原因的管理行动往往被混淆。我们旨在使用分子微生物学方法确定澳大利亚最大城市悉尼的高度城市化海滩玫瑰湾内粪便污染的原因、空间范围和点源。在一次显著的（67.5毫米）降雨过程中，在玫瑰湾海滩9个雨水沟的横断面网络上进行了采样，在降雨前6天、首次降雨当天（3.8毫米）、43毫米降雨后3天和降雨后4天进行采样。定量PCR（qPCR）用于靶向已被证明对人类粪便（污水）具有特异性的细菌（即钩端螺旋菌科和拟杆菌科）的标记基因，以及分别对鸟和狗粪便具有特异性的Heliobacter和Bacteroides的基因序列，以及ARGs（sulI、tetA、qnrS、dfrA1和vanB）。16S rRNA基因扩增子测序也被用于区分粪便污染的微生物特征。在降雨之前，FIB水平较低（平均值：2.4 CFU/100 ml）伴随着人类和动物粪便标志物水平普遍较低，但一个样带除外，这可能表明天气干燥，污水泄漏。在43毫米的降雨之后，雨水排水沟和海水样本中的人类粪便标志物水平显著增加，这些标志物的最高水平将几个雨水排水沟确定为污水污染源。在此期间，在距离海岸1000米的地方观察到污水污染，并且与ARGs dfrA1、qnrS、sulI和vanB的水平通常高度升高显著正相关。此时，雨水排水沟中的狗粪标记物水平显著升高，这也表明降雨导致周围集水区的狗粪物质输入增加。使用16S rRNA基因扩增子测序，确定了几个雨水污染的指示分类群，如Arcobacter spp.和Comamonadaceae spp.，并使用Bayesian SourceTracker工具对特定雨水排放对周围环境的相对影响进行建模，揭示了在降雨事件的不同时期，离散雨水排水沟的异质性贡献，其中一个特定排水沟的微生物特征贡献了直接相邻海水中高达50%的细菌群落。通过应用一系列分子微生物学方法，我们精确地确定了城市化海滩粪便污染和其他相关微生物危害（如ARGs）的原因和点源，这有助于确定最适合对海滩水质进行有针对性管理的地点。
Abstract
Urbanised beaches are regularly impacted by faecal pollution, but management actions to resolve the causes of contamination are often obfuscated by the inability of standard Faecal Indicator Bacteria (FIB) analyses to discriminate sources of faecal material or detect other microbial hazards, including antibiotic resistance genes (ARGs). We aimed to determine the causes, spatial extent, and point sources of faecal contamination within Rose Bay, a highly urbanised beach within Sydney, Australia's largest city, using molecular microbiological approaches. Sampling was performed across a network of transects originating at 9 stormwater drains located on Rose Bay beach over the course of a significant (67.5 mm) rainfall event, whereby samples were taken 6 days prior to any rain, on the day of initial rainfall (3.8 mm), three days later after 43 mm of rain and then four days after any rain. Quantitative PCR (qPCR) was used to target marker genes from bacteria (i.e., Lachnospiraceae and Bacteroides) that have been demonstrated to be specific to human faeces (sewage), along with gene sequences from Heliobacter and Bacteriodes that are specific to bird and dog faeces respectively, and ARGs (sulI, tetA, qnrS, dfrA1 and vanB). 16S rRNA gene amplicon sequencing was also used to discriminate microbial signatures of faecal contamination. Prior to the rain event, low FIB levels (mean: 2.4 CFU/100 ml) were accompanied by generally low levels of the human and animal faecal markers, with the exception of one transect, potentially indicative of a dry weather sewage leak. Following 43 mm of rain, levels of both human faecal markers increased significantly in stormwater drain and seawater samples, with highest levels of these markers pinpointing several stormwater drains as sources of sewage contamination. During this time, sewage contamination was observed up to 1000 m from shore and was significantly and positively correlated with often highly elevated levels of the ARGs dfrA1, qnrS, sulI and vanB. Significantly elevated levels of the dog faecal marker in stormwater drains at this time also indicated that rainfall led to increased input of dog faecal material from the surrounding catchment. Using 16S rRNA gene amplicon sequencing, several indicator taxa for stormwater contamination such as Arcobacter spp. and Comamonadaceae spp. were identified and the Bayesian SourceTracker tool was used to model the relative impact of specific stormwater drains on the surrounding environment, revealing a heterogeneous contribution of discrete stormwater drains during different periods of the rainfall event, with the microbial signature of one particular drain contributing up to 50% of bacterial community in the seawater directly adjacent. By applying a suite of molecular microbiological approaches, we have precisely pinpointed the causes and point-sources of faecal contamination and other associated microbiological hazards (e.g., ARGs) at an urbanised beach, which has helped to identify the most suitable locations for targeted management of water quality at the beach.

https://www.sciencedirect.com/science/article/abs/pii/S0043135422004870