Document Type

Thesis - University Access Only

Award Date

2005

Degree Name

Master of Science (MS)

Department / School

Biology and Microbiology

Abstract

Water pollution by fecal material is an increasingly important issue throughout the United States. A well-established biological indicator of fecal pollution is the bacterium Escherichia coli, an inhabitant of the intestinal tracts of warm-blooded animals. If E. coli is found in water supplies in South Dakota, it indicates fecal contamination of the water, since the bacterium is not normally found as a native microorganism in soils or waters from this part of the world. However, traditional methods have not been able to discern whether E. coli in contaminated water is either from a human or non-human source. The past 20 years have provided a dramatic growth in bacterial source tracking methods, one goal of which is to develop and use reliable methods to identify the source of E. coli in surface waters. For the study described, antibiotic resistance analysis (ARA) of E. coli strains from human and animal sources was used to see if ARA patterns of E. coli strains from different hosts and ecoregions in South Dakota differed significantly. Use of ARA analysis requires that a database of bacterial isolates be constructed as a reference before the likely origin of E. coli found in the surface waters can be evaluated. In this study, a database of approximately 2800 E. coli isolates from seven different host sources from four different ecoregions in South Dakota was constructed. The four ecoregions studied were the Middle Rockies, Northwestern Glaciated Plains, Northwestern Great Plains, and Northern Glaciated Plains. E. coli strains were isolated from fresh, raw fecal material or wastewater influent samples using mFC agar and Chromagar plates. An EC-MUG assay was performed to confirm that each bacterial strain isolated on the plating media was E. coli. Isolates were sent to another laboratory for ARA, and the results and database were sent back to us for discriminant analysis. The average rate of correct classification (ARCC) for the library, not taking into account the four ecoregions, was 32.6%. When ecoregions were taken into account, the ARCC increased by an average a 9.75%. When only human and non-human sources were compared without taking into account the ecoregions, the ARCC was 65.3%. When the ecoregions were included the ARCC increased by an average of 3.3%. Two sets of unknown samples (eight total; four per set) were collected. These were termed suspected unknowns and true unknowns. The suspected unknowns were water samples taken from a stream where there was a strong indication of what species may be the main source of pollution. The true unknowns were water samples taken without regard as to the source of contamination. The ARCC of both sets of unknowns was 14.3%. The Minimum Detectable Percentage that was calculated for the data was 26.44%. This means that any source that resulted in a rate of correct classification over 26.44% was a real number. The instance of this happening occurred in all eight unknown samples at least for one source animal, and in some cases two sources were deemed real. Classification across an entire state may be difficult due to different ecoregions. Ecoregion differences may have an effect on the gut fauna of these animals. Other ARA studies have shown higher ARCC's, but they have used smaller study areas or different microbes. Although having a fairly good discriminatory power for human and non-human sources, the multispecies accuracy of this method may be of concern. However, ARA would provide a cost-effective screening tool. The database was submitted to the South Dakota Department of Environment and Natural Resources and the State Health Department for use in monitoring South Dakota water supplies for fecal contamination. In the future, a more powerful method may be used as a second-tier BST method to discriminate further between species that contribute to fecal contamination of water.

Library of Congress Subject Headings

Enterobacteriaceae
Escherichia coli
Bacterial pollution of water -- South Dakota
Water quality management -- South Dakota
Drug resistance in microorganisms

Format

application/pdf

Number of Pages

202

Publisher

South Dakota State University

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