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Phenotypic library-based microbial source tracking methods: efficacy in the California collaborative study.

Valerie J Harwood1, Bruce Wiggins, Charles Hagedorn

  • 1Department of Biology, SCA 110, University of South Florida, Tampa, FL 33620, USA.

Journal of Water and Health
|September 24, 2004
PubMed
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This study evaluated phenotypic subtyping methods for microbial source tracking (MST). Antibiotic resistance analysis (ARA) of fecal streptococci proved most accurate for identifying fecal contamination sources in water.

Area of Science:

  • Environmental microbiology
  • Water quality assessment
  • Bacterial subtyping

Background:

  • Microbial source tracking (MST) is crucial for identifying fecal contamination in water bodies.
  • Phenotypic subtyping methods, including antibiotic resistance analysis (ARA), multiple antibiotic resistance (MAR), and carbon source utilization, were employed.
  • These techniques analyze indicator bacteria like fecal streptococci, enterococci, fecal coliforms, and E. coli.

Purpose of the Study:

  • To assess the accuracy of library-based phenotypic subtyping for identifying fecal sources in water samples.
  • To compare the effectiveness of different subtyping methods, including ARA, MAR, and carbon source utilization.
  • To evaluate the impact of a minimum detectable percentage (MDP) cut-off on source identification accuracy.

Main Methods:

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  • Fecal samples from known sources (human, sewage, cattle, dogs, gulls) and seeded water samples were analyzed.
  • Libraries of phenotypic patterns were created from indicator bacteria isolated from known sources.
  • Methods included ARA, MAR, Kirby-Bauer susceptibility testing, and carbon source utilization.
  • Source prediction accuracy was assessed with and without a minimum detectable percentage (MDP).

Main Results:

  • Antibiotic resistance analysis (ARA) of fecal streptococci demonstrated the highest accuracy (100% true-positive, 39% false-positive with MDP).
  • Phenotypic subtyping methods were generally more prone to false-positive than false-negative errors.
  • The use of a MDP reduced false-positive identifications without significantly impacting true-positives in accurate libraries.
  • Internal library accuracy did not reliably predict external source prediction capabilities.

Conclusions:

  • ARA of fecal streptococci is a highly accurate method for fecal source identification in water.
  • Phenotypic subtyping requires careful validation, as internal library metrics may not reflect predictive accuracy.
  • The minimum detectable percentage (MDP) is a useful parameter for reducing false-positive results in MST.