As part of a larger microbial source tracking (MST) study, several laboratories used library-based, phenotypic subtyping techniques to analyse fecal samples from known sources (human, sewage, cattle, dogs and gulls) and blinded water samples that were contaminated with the fecal sources. The methods used included antibiotic resistance analysis (ARA) of fecal streptococci, enterococci, fecal coliforms and E. coli; multiple antibiotic resistance (MAR) and Kirby-Bauer antibiotic susceptibility testing of E. coli; and carbon source utilization for fecal streptococci and E. coli. Libraries comprising phenotypic patterns of indicator bacteria isolated from known fecal sources were used to predict the sources of isolates from water samples that had been seeded with fecal material from the same sources as those used to create the libraries. The accuracy of fecal source identification in the water samples was assessed both with and without a cut-off termed the minimum detectable percentage (MDP). The libraries (∼300 isolates) were not large enough to avoid the artefact of source-independent grouping, but some important conclusions could still be drawn. Use of a MDP decreased the percentage of false-positive source identifications, and had little effect on the high percentage of true-positives in the most accurate libraries. In general, the methods were more prone to false-positive than to false-negative errors. The most accurate method, with a true-positive rate of 100% and a false-positive rate of 39% when analysed with a MDP, was ARA of fecal streptococci. The internal accuracy of the libraries did not correlate with the accuracy of source prediction in water samples, showing that one should not rely solely on parameters such as the average rate of correct classification of a library to indicate its predictive capabilities.
Skip Nav Destination
Article navigation
Research Article|
December 01 2003
Phenotypic library-based microbial source tracking methods: Efficacy in the California collaborative study
Valerie J. Harwood;
Valerie J. Harwood
1Department of Biology, SCA 110, University of South Florida, 4202 E. Fowler Ave, Tampa, FL 33620, USA
Search for other works by this author on:
Bruce Wiggins;
Bruce Wiggins
2James Madison University, Harrisonburg, VA 22807, USA
Search for other works by this author on:
Charles Hagedorn;
Charles Hagedorn
3Virginia Polytechnic and State University, Blacksburg, VA 24061, USA
Search for other works by this author on:
R. D. Ellender;
R. D. Ellender
4University of Southern Mississippi, Hattiesburg, MS 39406, USA
Search for other works by this author on:
James Kern;
James Kern
6Maptech Inc., Blacksburg, VA 24060, USA
Search for other works by this author on:
Mansour Samadpour;
Mansour Samadpour
7Institute for Environmental Health, 8279 Lake City Way NE, Seattle WA 98115, USA
Search for other works by this author on:
Annie C. H. Chapman;
Annie C. H. Chapman
3Virginia Polytechnic and State University, Blacksburg, VA 24061, USA
Search for other works by this author on:
Brian J. Robinson;
Brian J. Robinson
4University of Southern Mississippi, Hattiesburg, MS 39406, USA
Search for other works by this author on:
Brian C. Thompson
Brian C. Thompson
5NOAA, Charleston, SC 29412, USA
Search for other works by this author on:
J Water Health (2003) 1 (4): 153–166.
Citation
Valerie J. Harwood, Bruce Wiggins, Charles Hagedorn, R. D. Ellender, Jan Gooch, James Kern, Mansour Samadpour, Annie C. H. Chapman, Brian J. Robinson, Brian C. Thompson; Phenotypic library-based microbial source tracking methods: Efficacy in the California collaborative study. J Water Health 1 December 2003; 1 (4): 153–166. doi: https://doi.org/10.2166/wh.2003.0018
Download citation file: