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运用基于双重基因组的方法,在基流和暴雨流事件期间,追踪河口盐水中的微生物来源,并识别粪便污染模式。

Microbial source tracking and identification of fecal contamination patterns in saltwater estuaries between base- and storm-flow events using dual genome-based approaches.

机构信息

Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China.

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

出版信息

Sci Total Environ. 2024 Dec 1;954:176704. doi: 10.1016/j.scitotenv.2024.176704. Epub 2024 Oct 2.

Abstract

Fecal contamination from natural and anthropogenic sources poses significant threats to saltwater estuaries, particularly after storms or heavy rainfall. Monitoring fecal contamination is essential for protecting these vulnerable ecosystems having important ecological and economic values. In this study, we investigated the abundance, sources, and potential causes of fecal contamination at three marine and seven freshwater stations across Vaughn Bay (WA, USA), a shellfish growing district, during base- and storm-flow events. Additionally, we evaluated the performance of fecal indicator bacteria (FIB) quantification, optical brightener assessment, and qPCR analysis for fecal contamination quantification. We compared the effectiveness of qPCR-based microbial source tracking (MST), which targeted a broad range of hosts including, such as humans, birds, cows, horses, ruminants, dogs, and pigs, with sequencing-based MST in identifying fecal contamination sources. Both MST analysis approaches identified birds and humans as the primary sources of fecal contamination. For marine water stations, freshwater creeks VBU001, VBU002, and VB047, along with drain VB007, were identified as the main sources of human-derived fecal contamination in Vaughn Bay, based on Kendall's tau analysis (τ: 0.58-0.97). This information indicates that the septic systems in the catchment areas of these creeks and drains require further investigation to achieve effective fecal contamination control. Optical brightener, FIB enumeration and qPCR quantification results were generally higher during storm-flow events, although they showed poor correlation with each other (Pearson r < 0.40), likely due to physiological and phylogenetic differences among the target organisms of these methods. However, the sequencing-based method faces challenges in precise quantitative identification of differences in fecal contamination between base- and storm-flow events. Due to its high-throughput and cost-effectiveness, we recommend using sequencing-based analysis for large-scale identification of the primary sources of fecal contamination in water environments, followed by targeted qPCR quantification of MST markers for more precise assessments.

摘要

天然和人为来源的粪便污染对盐水河口,特别是在风暴或大雨之后,构成了重大威胁。监测粪便污染对于保护这些具有重要生态和经济价值的脆弱生态系统至关重要。在本研究中,我们在沃恩湾(美国华盛顿州)的三个海洋和七个淡水站调查了粪便污染的丰度、来源和潜在原因,这些地点在基础流和风暴流事件中都有涉及。此外,我们评估了粪便指示细菌(FIB)量化、光学增白剂评估和用于粪便污染量化的 qPCR 分析的性能。我们比较了基于 qPCR 的微生物源追踪(MST)的有效性,该方法针对包括人类、鸟类、牛、马、反刍动物、狗和猪在内的广泛宿主进行了靶向,以及基于测序的 MST 用于识别粪便污染来源。这两种 MST 分析方法都将鸟类和人类确定为粪便污染的主要来源。对于海洋水站,根据 Kendall tau 分析(τ:0.58-0.97),淡水溪流 VBU001、VBU002 和 VB047 以及污水 VB007 被确定为沃恩湾中人类粪便污染的主要来源。这表明,这些溪流和污水渠集水区的化粪池系统需要进一步调查,以实现有效的粪便污染控制。尽管光学增白剂、FIB 计数和 qPCR 定量结果在风暴流事件中通常更高,但它们彼此之间的相关性较差(Pearson r<0.40),这可能是由于这些方法的目标生物之间存在生理和系统发育差异。然而,基于测序的方法在精确量化基础流和风暴流事件之间粪便污染差异方面面临挑战。由于其高通量和成本效益,我们建议在大规模识别水环境中粪便污染的主要来源时使用基于测序的分析,然后针对 MST 标记进行靶向 qPCR 定量,以进行更精确的评估。

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