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Abstract: Contamination of recreational waters with Escherichia coli and Enterococcus sp. is a widespread problem resulting in beach closures and loss of recreational activity. While E. coli is frequently used as an indicator of fecal contamination, and has been extensively measured in waterways, few studies have examined the presence of potentially pathogenic E. coli strains in beach waters. In this study, a combination of high-throughput, robot-assisted colony hybridization and PCR-based analyses were used to determine the genomic composition and frequency of virulence genes present in E. coli isolated from beach water in Avalon Bay, Santa Catalina Island, CA. A total of 24,493 E. coli isolates were collected from two sites at a popular swimming beach between August through September 2007 and from July through August 2008. All isolates were examined for the presence of shiga-like toxins (stx1/stx2), intimin (eaeA), and enterotoxins (ST/LT). Of the 24,493 isolates examined, 3.6% contained the eaeA gene, indicating that these isolates were potential EPEC strains. On five dates, however, greater than 10% of the strains were potential EPEC, suggesting that incidence of virulence genes at this beach has a strong temporal component. No STEC or ETEC isolates were detected, and only eight (<1.0%) of the potential EPEC isolates were found to carry the EAF plasmid. The potential EPEC isolates mainly belonged to E. coli phylogenetic groups B1 or B2, and carried the β intimin subtype. DNA fingerprint analyses of the potential EPEC strains indicated that the isolates belonged to several genetically diverse groups, although clonal isolates were frequently detected. While the presence of virulence genes alone cannot be used to determine the pathogenicity of strains, results from this study show that potential EPEC strains can be found in marine beach water and their presence needs to be considered as one of the factors used in decisions concerning beach closures. [ABSTRACT FROM AUTHOR]

The study used existing indicator bacterial data and a number of physicochemical parameters that can be measured instantaneously to determine if a decision tree approach, especially classification and regression tree, could be used to predict bacterial concentrations in timely manner for beach closure management. Each indicator bacteria showed different tree structures and each had its own significant variables; Dissolved oxygen played an important role for both total coliform and fecal coliform and turbidity was the most important factor to predict concentrations of enterococci for decision tree approaches. Root mean squared error stayed between 5 and 6.5% of the average values of observations; RMSEs from each simulation, 0.25 for total coliform, 0.31 for fecal coliform, and 0.29 for enterococci. Estimations from tree structures would be regarded as a good representation of the actual data. In addition to results of the objective function, RMSE, 77.5% of actual value fell into the 95% of confidence interval of estimations for total coliform concentrations, 60% for fecal coliform concentrations, and 62.5% for enterococci concentrations. The approach showed reliable estimations for the majority of the data processed, although the method did not portray low concentrations of bacteria as well. [ABSTRACT FROM AUTHOR]