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A Microbial Signature Approach to Identify Fecal Pollution in the Waters Off an Urbanized Coast of Lake Michigan

  • Environmental Microbiology
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Abstract

Urban coasts receive watershed drainage from ecosystems that include highly developed lands with sewer and stormwater infrastructure. In these complex ecosystems, coastal waters are often contaminated with fecal pollution, where multiple delivery mechanisms that often contain multiple fecal sources make it difficult to mitigate the pollution. Here, we exploit bacterial community sequencing of the V6 and V6V4 hypervariable regions of the bacterial 16S rRNA gene to identify bacterial distributions that signal the presence of sewer, fecal, and human fecal pollution. The sequences classified to three sewer infrastructure-associated bacterial genera, Acinetobacter, Arcobacter, and Trichococcus, and five fecal-associated bacterial families, Bacteroidaceae, Porphyromonadaceae, Clostridiaceae, Lachnospiraceae, and Ruminococcaceae, served as signatures of sewer and fecal contamination, respectively. The human fecal signature was determined with the Bayesian source estimation program SourceTracker, which we applied to a set of 40 sewage influent samples collected in Milwaukee, WI, USA to identify operational taxonomic units (≥97 % identity) that were most likely of human fecal origin. During periods of dry weather, the magnitudes of all three signatures were relatively low in Milwaukee’s urban rivers and harbor and nearly zero in Lake Michigan. However, the relative contribution of the sewer and fecal signature frequently increased to >2 % of the measured surface water communities following sewer overflows. Also during combined sewer overflows, the ratio of the human fecal pollution signature to the fecal pollution signature in surface waters was generally close to that of sewage, but this ratio decreased dramatically during dry weather and rain events, suggesting that nonhuman fecal pollution was the dominant source during these weather-driven scenarios. The qPCR detection of two human fecal indicators, human Bacteroides and Lachno2, confirmed the urban fecal footprint in this ecosystem extends to at least 8 km offshore.

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Acknowledgments

The authors would like to thank Jessica VandeWalle, Elizabeth Sauer, Colin Peake, and Sabrina Mueller-Spitz for assistance with sample collection and processing. We also thank Sharon Grim and Joseph Vineis for the DNA sequence library preparation and data curation. Special thanks go to Dan Knights who provided an unreleased version of SourceTracker, so we could identify source probabilities for individual OTUs. We also thank Linda Sackett for providing a supportive environment for discussion of this work. Finally, we would like to thank two anonymous reviewers whose comments greatly improved the clarity of this manuscript. Financial support for this work was provided by the University of Wisconsin Sea Grant Institute under grants from the National Sea Grant College Program, NOAA, the U.S. Department of Commerce, and the State of Wisconsin, grant #NA10OAR4170070 to SLM and the National Institutes of Health grant #1R01AI091829-01A1 to SLM and MLS.

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Authors and Affiliations

  1. Great Lakes WATER Institute, School of Freshwater Sciences, University of Wisconsin—Milwaukee, 600 E. Greenfield Ave, Milwaukee, WI, 53204, USA

    Ryan J. Newton, Melinda J. Bootsma & Sandra L. McLellan

  2. Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, MA, 02543, USA

    Hilary G. Morrison & Mitchell L. Sogin

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  1. Ryan J. Newton
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  2. Melinda J. Bootsma
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Correspondence to Sandra L. McLellan.

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Newton, R.J., Bootsma, M.J., Morrison, H.G. et al. A Microbial Signature Approach to Identify Fecal Pollution in the Waters Off an Urbanized Coast of Lake Michigan. Microb Ecol 65, 1011–1023 (2013). https://doi.org/10.1007/s00248-013-0200-9

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