Optimization and validation of rep-PCR genotypic libraries for microbial source tracking of environmental Escherichia coli isolates

Abstract

Escherichia coli can be used to help identify sources of fecal contamination in the environment. Escherichia coli genotypic fecal libraries and pattern-matching algorithms were assessed for their effectiveness in correctly identifying sources. Fecal samples (n = 172) were collected from various sources from three agricultural landscapes in Canada. Escherichia coli isolates were fingerprinted using BOX- and enterobacterial repetitive intergenic consensus (ERIC) - polymerase chain reaction primers, revealing 769 and 1 057 distinct genotypes, respectively, for the 9 047 isolates collected in 2004 in Ontario. The average rate of correct classification (ARCC) was comparable for BOX- (48%) and ERIC-based (62%) libraries and between libraries with clones removed per sample (55%) and clones removed per unit (54%). ARCC increased with fewer classification units (from 44% to 65%). ARCC for k-nearest neighbour (64%) and maximum similarity (60%) algorithms were comparable, but maximum similarity had better sensitivity and specificity than k-nearest neighbour. Geographical and temporal shifts in community composition resulted in loss of accuracy. Several ERIC genotypes (n = 112) were common between sources and were removed from the library, improving ARCC (77%). The latter library proved to be more accurate, but its accuracy with respect to sourcing environmental isolates remains to be tested.