The development of a methodology to identify the origin of fecal pollution is important both for assessing the degree of risk posed to public health and for developing strategies to mitigate the environmental loading of pathogens associated with waterborne disease transmission. Five rep-PCR genomic fingerprinting methods, such as rep-PCR, enterobacterial repetitive intergenic consensus (ERIC)-PCR, ERIC2-PCR, BOX-PCR and (GTG)(5)-PCR, were assessed for their potential in differentiation of 232 fecal Escherichia coli isolates obtained from humans, poultry (chicken, duck and turkey) and wild birds (Canada goose and gull). Based on the results of cluster analysis and discriminant function analysis, (GTG)(5)-PCR was found to be the most suitable method for molecular typing of fecal E. coli, followed by BOX-PCR, REP-PCR, ERIC-PCR and ERIC2-PCR. A discriminant function analysis of (GTG)(5)-PCR fingerprints showed that 94.1%, 79.8%, 80.5%, 74.4%, 86.7% and 88.6% of turkey, chicken, duck, Canada goose, gull and human E. coli isolates were classified into the correct host group, respectively. Subsequently, (GTG)(5)-PCR was tested for its ability to track the origin of 113 environmental E. coli isolated from natural pond water. In conclusion, the (GTG)(5)-PCR genomic fingerprinting method can be considered as a promising genotypic tool for epidemiological surveillance of fecal pollution in aquatic environments.

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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.

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