Abstract
ABSTRACTMicrobial water quality is generally monitored by culturable fecal indicator bacteria (FIB), which are intended to signal human health risk due to fecal pollution. However, FIB have limited utility in most urbanized watersheds as they do not discriminate among fecal pollution sources, tend to make up a small fraction of the total microbial community, and do not inform on pollution impacts on the native ecosystem. To move beyond these limitations, we assessed entire bacterial communities and investigated how bacterial diversity relates to traditional ecological and human health-relevant water quality indicators throughout the Milwaukee River Basin. Samples were collected from 16 sites on 5 days during the summer, including both wet and dry weather events, and were processed by 16S rRNA gene amplicon sequencing. Historical water quality at each sampling location, as opposed to upstream land use, was associated significantly with bacterial community alpha diversity. Source partitioning the sequence data was important for determining water quality relationships. Sewage-associated bacterial sequences were detected in all samples, and the relative abundance of sewage sequences was strongly associated with the human Bacteroides fecal marker. From this relationship, we developed a preliminary threshold for human sewage pollution when using bacterial community sequence data. Certain abundant freshwater bacterial sequences were also associated with human fecal pollution, suggesting their possible utility in water quality monitoring. This study sheds light on how bacterial community analysis can be used to supplement current water quality monitoring techniques to better understand interactions between ecological water quality and human health indicators.IMPORTANCE Surface waters in highly developed mixed-use watersheds are frequently impacted by a wide variety of pollutants, leading to a range of impairments that must be monitored and remediated. With advancing technologies, microbial community sequencing may soon become a feasible method for routine evaluation of the ecological quality and human health risk of a water body. In this study, we partnered with a local citizen science organization to evaluate the utility of microbial community sequencing for identifying pollution sources and ecological impairments in a large mixed-use watershed. We show that changes in microbial community diversity and composition are indicative of both long-term ecological impairments and short-term fecal pollution impacts. By source partitioning the sequence data, we also estimate a threshold target for human sewage pollution, which may be useful as a starting point for future development of sequencing-based water quality monitoring techniques.
Highlights
Mixed-use watersheds can be impaired by pollutants from many different sources, such as urban runoff, sewage overflows, agricultural runoff, livestock, or wildlife
Current microbial water quality monitoring methods based on detection of culturable fecal indicator bacteria (FIB) can produce highly variable results, suggesting that evaluating a single indicator may not be appropriate for determining health risk [1, 2]
The Milwaukee River watershed is a large mixed-land-use watershed containing a total of 875 miles of stream reaches that divide into three main rivers, the Milwaukee, Menomonee, and Kinnickinnic Rivers, which flow into the Milwaukee harbor estuary and Lake Michigan
Summary
Mixed-use watersheds can be impaired by pollutants from many different sources, such as urban runoff, sewage overflows, agricultural runoff, livestock, or wildlife These sources can contribute a range of pollutants, including pathogens, sediment, or nutrients, which can lead to deteriorating ecological water quality and/or increased. As water environments are often highly complex, with a mix of active or inactive community members and contributions from various natural or anthropogenic sources, observations of bulk microbial community composition may not be appropriate for identifying pollutant monitoring targets, especially when pollutants may be present at low levels. Methods to utilize sequencing data for pollution tracking, such as SourceTracker [28] and FORENSIC [29, 30], are being developed While these approaches are useful, they are limited by a need for input of both pollutant and environmental community data (SourceTracker) or limited fecal pollution targets (FORENSIC), and neither method has been connected to health risk. By assessing changes in microbial community diversity and partitioning communities against curated databases, we provide insights into how DNA sequencing data can be incorporated into monitoring frameworks for both ecological and human health
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