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This article in JEQ

  1. Vol. 41 No. 2, p. 534-543
    Received: May 10, 2011

    * Corresponding author(s): aunc@nmsu.edu
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Microarray Assessment of Virulence, Antibiotic, and Heavy Metal Resistance in an Agricultural Watershed Creek

  1. Adrian Unc *ac,
  2. Ludek Zurekb,
  3. Greg Petersonb,
  4. Sanjeev Narayananb,
  5. Susan V. Springthorpec and
  6. Syed A. Sattarc
  1. a Dep. of Plant and Environmental Sciences, New Mexico State Univ., Las Cruces, NM 88003
    c Centre for Research on Environmental Microbiology, Univ. of Ottawa, Ottawa, ON K1H 8M5, Canada. Assigned to Associate Editor Ed Topp
    b Dep. of Diagnostic Medicine and Pathobiology, Kansas State Univ., Manhattan, KS 66506


Potential risks associated with impaired surface water quality have commonly been evaluated by indirect description of potential sources using various fecal microbial indicators and derived source-tracking methods. These approaches are valuable for assessing and monitoring the impacts of land-use changes and changes in management practices at the source of contamination. A more detailed evaluation of putative etiologically significant genetic determinants can add value to these assessments. We evaluated the utility of using a microarray that integrates virulence genes with antibiotic and heavy metal resistance genes to describe and discriminate among spatially and seasonally distinct water samples from an agricultural watershed creek in Eastern Ontario. Because microarray signals may be analyzed as binomial distributions, the significance of ambiguous signals can be easily evaluated by using available off-the-shelf software. The FAMD software was used to evaluate uncertainties in the signal data. Analysis of multilocus fingerprinting data sets containing missing data has shown that, for the tested system, any variability in microarray signals had a marginal effect on data interpretation. For the tested watershed, results suggest that in general the wet fall season increased the downstream detection of virulence and resistance genes. Thus, the tested microarray technique has the potential to rapidly describe the quality of surface waters and thus to provide a qualitative tool to augment quantitative microbial risk assessments.

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