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

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.

Large-scale sampling of the freshwater microbiome suggests pollution-driven ecosystem changes

Freshwater microbes play a crucial role in the global carbon cycle. Anthropogenic stressors that lead to changes in these microbial communities are likely to have profound consequences for freshwater ecosystems. Using field data from the coordinated sampling of 617 lakes, ponds, rivers, and streams by citizen scientists, we observed linkages between microbial community composition, light and chemical pollution, and greenhouse gas concentration. All sampled water bodies were net emitters of CO₂, with higher concentrations in running waters, and increasing concentrations at higher latitudes. Light pollution occurred at 75% of sites, was higher in urban areas and along rivers, and had a measurable effect on the microbial alpha diversity. Genetic elements suggestive of chemical stress and antimicrobial resistances (IntI1, blaOX₅₈) were found in 85% of sites, and were also more prevalent in urban streams and rivers. Light pollution and CO₂ were significantly related to microbial community composition, with CO₂ inversely related to microbial phototrophy. Results of synchronous nationwide sampling indicate that pollution-driven alterations to the freshwater microbiome lead to changes in CO₂ production in natural waters and highlight the vulnerability of running waters to anthropogenic stressors.