Longitudinal Analysis of Urban Stormwater Microbiome and Resistome from Watersheds with and without Green Infrastructure using Long-Read Sequencing

被引:1
|
作者
Mills, Molly [1 ]
Davis, Angela [2 ,9 ]
Lancaster, Emma [2 ]
Choi, Boseung [3 ]
Martin, Jay [2 ,4 ,5 ]
Winston, Ryan [4 ,6 ]
Lee, Jiyoung [1 ,7 ,8 ]
机构
[1] Ohio State Univ, Coll Publ Hlth, Div Environm Hlth Sci, Columbus, OH 43210 USA
[2] Ohio State Univ, Environm Sci Grad Program, Columbus, OH USA
[3] Korea Univ, Div Big Data Sci, Sejong, South Korea
[4] Ohio State Univ, Dept Food Agr & Biol Engn, Columbus, OH USA
[5] Ohio State Univ, Sustainabil Inst, Columbus, OH USA
[6] Ohio State Univ, Dept Civil Environm & Geodet Engn, Columbus, OH USA
[7] Ohio State Univ, Dept Food Sci & Technol, Columbus, OH 43210 USA
[8] Ohio State Univ, Infect Dis Inst, Columbus, OH 43210 USA
[9] US EPA, Off Groundwater & Drinking Water, Off Water, Washington, DC USA
基金
美国国家科学基金会;
关键词
urban runoff; microbial source tracking; bioretention; permeable pavement; antibiotic resistance; One Health; QUANTITATIVE DETECTION; FECAL CONTAMINATION; GENETIC-MARKERS; BACTEROIDALES; PATHOGENS; BACTERIA; BEACHES;
D O I
10.1016/j.watres.2024.121873
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Since stormwater conveys a variety of contaminants into water bodies, green infrastructure (GI) is increasingly being adopted as an on-site treatment solution in addition to controlling peak flows. The purpose of this study was to identify differences in microbial water quality of stormwater in watersheds retrofitted with GI vs. those without GI. Considering stormwater is recently recognized as a contributor to the antibiotic resistance (AR) threat, another goal of this study was to characterize changes in the microbiome and collection of AR genes (resistome) of urban stormwater with season, rainfall characteristics, and fecal contamination. MinION long-read sequencing was used to analyze stormwater microbiome and resistome from watersheds with and without GI in Columbus, Ohio, United States, over 18 months. We characterized fecal contamination in stormwater via culturing Escherichia coli and with molecular microbial source tracking (MST) to identify sources of fecal contamination. Overall, season and storm event (rainfall) characteristics had the strongest relationships with changes in the stormwater microbiome and resistome. We found no significant differences in microbial water quality or the microbiome of stormwater in watersheds with and without GI implemented. However, there were differences between the communities of microorganisms hosting antibiotic resistance genes (ARGs) in stormwater from watersheds with and without GI, indicating the potential sensitivity of AR bacteria to treatment. Stormwater was contaminated with high concentrations of human-associated fecal bacterial genes, and the ARG host bacterial community had considerable similarities to human feces/wastewater. We also identified 15 potential pathogens hosting ARGs in these stormwater resistome, including vancomycin-resistant Enterococcus faecium (VRE) and multidrug-resistant Pseudomonas aeruginosa. In summary, urban stormwater is highly contaminated and has a great potential to spread AR and microbial hazards to nearby environments. This study presents the most comprehensive analysis of stormwater microbiome and resistome to date, which is crucial to understanding the potential microbial risk from this matrix. This information can be used to guide future public health policy, stormwater reuse programs, and urban runoff treatment initiatives.
引用
收藏
页数:12
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