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Original Articles

The use of carbon-utilization profiling to determine sources of fecal contamination in a central Texas watershed

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Pages 104-113 | Published online: 23 Jul 2010
 

Abstract

The purpose of this research was to characterize the relationship of Escherichia coli isolates from various animals, sewage, and water based on carbon substrate utilization patterns, and to use these patterns to determine the dominant contributors of nonpoint source fecal pollution to a central Texas reservoir from its watershed. We collected 1028 fecal samples from cattle, companion animals, goat, horse, poultry, sewage, sheep, and wildlife, collectively. From these, 1915 E. coli fecal isolates were analyzed. We collected 100 water samples throughout the North Bosque watershed; 910 E. coli water isolates were analyzed. The Biolog system was used to generate a carbon-utilization pattern for each isolate. A dendrogram constructed from the carbon-utilization patterns demonstrated that isolates from the same source category usually clustered together, excluding water isolates that were spread over many clusters. A bacterial-source tracking library was constructed from the carbon-utilization data obtained from the fecal and sewage isolates and analyzed for internal accuracy. Rates of correct classification for the library ranged from 12.8 to 78.6%. The average rate of correct classification for the library was 45.8%, and specificity values were high, ranging from 75 to 99%. When water isolates were submitted to the library for identification, 43 were classified as originating from cattle, indicating cattle were the dominant source of fecal pollution in the watershed. This was followed by sewage at 27%. Based on these data, our first recommendation for decreasing bacterial pollution in this watershed is to implement strategies that can reduce the contribution of fecal contamination from these 2 sources.

Acknowledgments

We wish to thank the numerous individuals who assisted with the collection of field samples and with the carbon-utilization profiling. This tremendous amount of data could not have been collected in a reasonable timeframe without your help.

Notes

*RCC's are shown in boldface.

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