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EXPERIMENTAL AND STATISTICAL EVALUATION OF BACTERIAL SOURCE TRACKING IN A SUBALPINE REGION BY REP-PCR DNA FINGERPRINTING

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  701P0104,  . (doi: 10.13031/2013.15806)
Authors:   J.M. Albert, J. Munakata Marr, L. Tenorio, R.L. Siegrist
Keywords:   Bacterial source tracking, Escherichia coli, DNA fingerprinting, image analysis, statistical analysis

This investigation evaluated statistical analyses of rep-PCR DNA fingerprints obtained from Escherichia coli, as a potential means to differentiate between possible sources of fecal contamination as well as to assess the effect of wastewater treatment processes on communities of Escherichia coli. Analytical reproducibility within a single lab, three statistical approaches to correlating biomarkers and host groups, and two methods to evaluate biomarker specificity were investigated using a genetic library of DNA fingerprints of Escherichia coli isolates from both human and non-human sources. GelCompar II and methods based on penalized discriminant analysis (PDA) and k-nearest neighbors (KNN) classification procedures were used to differentiate between ten human and non-human source groups within the DNA library. KNN performed significantly better than PDA in a jackknife analysis, though the differences between GelCompar II and the other two methods were not significant. GelCompar II and KNN both attained =90% correct classification in a holdout procedure and assigned the greatest probability to the correct collection location of a blind sample. The significance of assignments of DNA fingerprint patterns within the library was assessed using interpoint distances analysis, which indicated underlying coherency within source groups. A randomization procedure was used to assess classification bias, however these results were difficult to interpret as they were dependent on the amount of randomization and the classification procedure used. This investigation stresses the need to understand the limitations of both analytical and statistical methods used in bacterial source tracking efforts.

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