Direct comparison of four bacterial source tracking methods and use of composite data sets

Aims: Four bacterial source tracking (BST) methods, enterobacterial repetitive intergenic consensus sequence polymerase chain reaction (ERIC-PCR), automated ribotyping using HindIII, Kirby-Bauer antibiotic resistance analysis (KB-ARA) and pulsed-field gel electrophoresis (PFGE) were directly compared using the same collection of Escherichia coli isolates. The data sets from each BST method and from composite methods were compared for library accuracy and their ability to identify water isolates. Methods and Results: Potential sources of faecal pollution were identified by watershed sanitary surveys. Domestic sewage and faecal samples from pets, cattle, avian livestock, other nonavian livestock, avian wildlife and nonavian wildlife sources were collected for isolation of E. coli. A total of 2275 E. coli isolates from 813 source samples were screened using ERIC-PCR to exclude clones and to maximize library diversity, resulting in 883 isolates from 745 samples selected for the library. The selected isolates were further analysed using automated ribotyping with HindIII, KB-ARA and PFGE. A total of 555 E. coli isolates obtained from 412 water samples were analysed by the four BST methods. A composite data set of the four BST methods gave the highest rates of correct classification (RCCs) with the fewest unidentified isolates than any single method alone. RCCs for the four-method composite data set and a seven-way split of source classes ranged from 22% for avian livestock to 83% for domestic sewage. Two-method composite data sets were also found to be better than individual methods, having RCCs similar to the four-method composite and identification of the same major sources of faecal pollution. Conclusions: The use of BST composite data sets may be more beneficial than the use of single methods. Significance and Impact of the Study: This is one of the first comprehensive comparisons using composite data from several BST methods. While the four-method approach provided the most desirable BST results, the use of two-method composite data sets may yield comparable BST results while providing for cost, labour and time savings.