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Title: Temporal assessment of the impact of exposure to cow feces in two watersheds by multiple host-specific PCR assays

Author
item LEE, YONG-JIN - U.S. EPA
item MARIROSA, MOLINA - U.S. EPA
item SANTO DOMINGO, JORGE - U.S. EPA
item CYTERSKI, MICHAEL - U.S. EPA
item Endale, Dinku
item SHANKS, ORIN - U.S. EPA

Submitted to: Applied and Environmental Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/7/2008
Publication Date: 9/7/2008
Citation: Lee, Y., Marirosa, M., Santo Domingo, J.W., Cyterski, M., Endale, D.M., Shanks, O.C. 2008. Temporal assessment of the impact of exposure to cow feces in two watersheds by multiple host-specific PCR assays. Applied and Environmental Microbiology. 74(22):6839-6847.

Interpretive Summary: Fecal contamination of recreational, drinking and shellfish harvesting waters is a major global problem. Microbial Source Tracking (MST) is a methodology that attempts to match microbes from a polluted site with the animal-source of fecal contamination, using molecular genetic markers in the microbes to identify the origin of fecal pollution. This is important because the first step in stopping contamination is identifying the source of the pollutant. MST methods need to be accurate, sensitive and applicable across landscapes and over time. Scientists at the USEPA Office of Research and Development, National Exposure Research laboratory, Ecosystem Research Division, in Athens, GA, USEPA Office of Research and Development, National Risk Management Research Laboratory in Cincinnati, OH, and USDA-ARS J. Phil Campbell Sr., Natural Resource Conservation Center in Watkinsville, GA, investigated how detection of fecal indicators in agricultural watersheds, using MST, is affected by the their distribution across landscapes and over time. They studied two watersheds; one directly impacted by cattle fecal pollution and another impacted only through runoff. They used several kinds of genetic markers associated with microbes in cattle manure. In the watershed grazed by cattle, one specific marker was detected in 65% of the water and sediment samples, while several other markers were found in 32-37% of the same samples. The level of diverse markers found in samples from the watershed without cattle was much less. In the watershed grazed by cattle, the level of fecal contamination evidenced by the markers was related to temperature, while in the watershed without cattle, contamination was related to rainfall, which increases run-off. The scientists found that the use these types of molecular markers provided better sensitivity and accuracy for tracking cattle fecal contamination in surface waters than a traditionally used indicator micro-organism (enterococci). The results provide important insights into using microbial genetic markers to identify sources of fecal contamination. Information on this new tool can be used by local and state water quality managers to improve detection and reduction of fecal pollution of surface waters.

Technical Abstract: Microbial source tracking methods need to be accurate, sensitive and exhibit spatiotemporal stability to provide useful field application data. The objective of this study was to investigate the effect of spatial and temporal variability on the frequency of detecting 16S rDNA-based Bacterioidales and metagenomic PCR assays developed to track bovine fecal contamination. Each assay was tested with DNA extracts from water and sediment samples collected from watershed 1 (WS1) directly impacted by cattle fecal pollution and from watershed 2 (WS2) impacted only through runoff. The 16S rDNA-based ruminant-specific Bacteroidales marker CF128F was detected in 65% of the samples, while metagenomic markers Bac1, Bac2 and Bac5 were found in 32-37% of the same samples in WS1. In contrast, all molecular markers were detected in less than 6% of the samples in WS2, except for the 16S rDNA-based general Bacteroidales marker, Bac32F (53.3%). One-way analysis of variance revealed spatial stability in the occurrence of molecular markers in each watershed. Statistical analysis including stepwise binary logistic regression and multiple linear regression identified that temperature was the most significant predictor in WS1 indicating temporal variation of fecal source loads in WS1. On the other hand, precipitation was more important in WS2, which supports a rainfall-runoff model of the transport of fecal indicators. Enterococcal counts did not show correlations with the occurrence of each molecular marker, suggesting that the dynamics of fecal source tracking markers may not correlate with the densities of traditional indicators of fecal contamination. Overall, management practices and the sensitivity of selected molecular markers as well as spatiotemporal variability are important variables to consider in MST implementation.