Development of efficient techniques to discriminate the sources of E. coli in aquatic environments is essential to improve the surveillance of fecal pollution indicators, to develop strategies to identify the sources of fecal contamination, and to implement appropriate management practices to minimize gastrointestinal disease transmission. In this study the robustness of five different rep-PCR methods, such as REP-PCR, ERIC-PCR, ERIC2-PCR, BOX-PCR and (GTG)5-PCR were evaluated to discriminate 271 E. coli strains isolated from two watersheds (Lakelse Lake and Okanagan Lake) located in British Columbia, Canada. Cluster analysis of (GTG)5-PCR, BOX-PCR, REP-PCR, ERIC-PCR and ERIC2-PCR profiles of 271 E. coli revealed 43 clusters, 35 clusters, 28 clusters, 23 clusters and 14 clusters, respectively. The discriminant analysis of rep-PCR genomic fingerprints of 271 E. coli isolates yielded an average rate of correct classification (watershed-specific) of 86.8%, 82.3%, 78.4%, 72.6% and 55.8% for (GTG)5-PCR, BOX-PCR, REP-PCR, ERIC-PCR and ERIC2-PCR, respectively. Based on the results of cluster analysis and discriminant function analysis, (GTG)5-PCR was found to be the most robust molecular tool for differentiation of E. coli populations in aquatic environments.
The Use of Artificial Neural Networks and a General Discriminant Analysis for Predicting Culling Reasons in Holstein-Friesian Cows Based on First-Lactation Performance Records
