A comparison of E. coli concentration estimates quantified by the EPA and a Michigan laboratory network using EPA Draft Method C.

We evaluated data from 10 laboratories that analyzed water samples from 82 recreational water sites across the state of Michigan between 2016 and 2018. Water sample replicates were analyzed by experienced U.S. Environmental Protection Agency (EPA) analysts and Michigan laboratories personnel, many of whom were newly trained, using EPA Draft Method C-a rapid quantitative polymerase chain reaction (qPCR) technique that provides same day Escherichia coli (E. coli) concentration results. Beach management decisions (i.e. remain open or issue an advisory or closure) based on E. coli concentration estimates obtained by Michigan labs and by the EPA were compared; the beach management decision agreed in 94% of the samples analyzed. We used the Wilcoxon one-sample signed rank test and nonparametric quantile regression to assess (1) the degree of agreement between E. coli concentrations quantified by Michigan labs versus the EPA and (2) Michigan lab E. coli measurement precision, relative to EPA results, in different years and water body types. The median quantile regression curve for Michigan labs versus EPA approximated the 1:1 line of perfect agreement more closely as years progressed. Similarly, Michigan lab E. coli estimates precision also demonstrated yearly improvements. No meaningful difference was observed in the degree of association between Michigan lab and EPA E. coli concentration estimates for inland lake and Great Lakes samples (median regression curve average slopes 0.93 and 0.95, respectively). Overall, our study shows that properly trained laboratory personnel can perform Draft Method C to a degree comparable with experienced EPA analysts. This allows health departments that oversee recreational water quality monitoring to be confident in qPCR results generated by the local laboratories responsible for analyzing the water samples.

Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C).

There is interest in the application of rapid quantitative polymerase chain reaction (qPCR) methods for recreational freshwater quality monitoring of the fecal indicator bacteria Escherichia coli (E. coli). In this study we determined the performance of 21 laboratories in meeting proposed, standardized data quality acceptance (QA) criteria and the variability of target gene copy estimates from these laboratories in analyses of 18 shared surface water samples by a draft qPCR method developed by the U.S. Environmental Protection Agency (EPA) for E. coli. The participating laboratories ranged from academic and government laboratories with more extensive qPCR experience to "new" water quality and public health laboratories with relatively little previous experience in most cases. Failures to meet QA criteria for the method were observed in 24% of the total 376 test sample analyses. Of these failures, 39% came from two of the "new" laboratories. Likely factors contributing to QA failures included deviations in recommended procedures for the storage and preparation of reference and control materials. A master standard curve calibration model was also found to give lower overall variability in log10 target gene copy estimates than the delta-delta Ct (ΔΔCt) calibration model used in previous EPA qPCR methods. However, differences between the mean estimates from the two models were not significant and variability between laboratories was the greatest contributor to overall method variability in either case. Study findings demonstrate the technical feasibility of multiple laboratories implementing this or other qPCR water quality monitoring methods with similar data quality acceptance criteria but suggest that additional practice and/or assistance may be valuable, even for some more generally experienced qPCR laboratories. Special attention should be placed on providing and following explicit guidance on the preparation, storage and handling of reference and control materials.

Standardized data quality acceptance criteria for a rapid Escherichia coli qPCR method (Draft Method C) for water quality monitoring at recreational beaches.

There is growing interest in the application of rapid quantitative polymerase chain reaction (qPCR) and other PCR-based methods for recreational water quality monitoring and management programs. This interest has strengthened given the publication of U.S. Environmental Protection Agency (EPA)-validated qPCR methods for enterococci fecal indicator bacteria (FIB) and has extended to similar methods for Escherichia coli (E. coli) FIB. Implementation of qPCR-based methods in monitoring programs can be facilitated by confidence in the quality of the data produced by these methods. Data quality can be determined through the establishment of a series of specifications that should reflect good laboratory practice. Ideally, these specifications will also account for the typical variability of data coming from multiple users of the method. This study developed proposed standardized data quality acceptance criteria that were established for important calibration model parameters and/or controls from a new qPCR method for E. coli (EPA Draft Method C) based upon data that was generated by 21 laboratories. Each laboratory followed a standardized protocol utilizing the same prescribed reagents and reference and control materials. After removal of outliers, statistical modeling based on a hierarchical Bayesian method was used to establish metrics for assay standard curve slope, intercept and lower limit of quantification that included between-laboratory, replicate testing within laboratory, and random error variability. A nested analysis of variance (ANOVA) was used to establish metrics for calibrator/positive control, negative control, and replicate sample analysis data. These data acceptance criteria should help those who may evaluate the technical quality of future findings from the method, as well as those who might use the method in the future. Furthermore, these benchmarks and the approaches described for determining them may be helpful to method users seeking to establish comparable laboratory-specific criteria if changes in the reference and/or control materials must be made.

Staphylococcus aureus and methicillin-resistant S. aureus (MRSA) at ambient freshwater beaches.

Methicillin-resistant Staphylococcus aureus (MRSA) are a threat to human health worldwide, and although detected at marine beaches, they have been largely unstudied at freshwater beaches. Genes indicating S. aureus (SA; femA) and methicillin resistance (mecA) were detected at 11 and 12 of 13 US Great Lakes beaches and in 18% or 27% of 287 recreational water samples, respectively. Eight beaches had mecA+femA (potential MRSA) detections. During an intensive study, higher bather numbers, staphylococci concentrations, and femA detections were found in samples collected after noon than before noon. Local population density, beach cloud cover, and beach wave height were significantly correlated with SA or MRSA detection frequency. The Panton-Valentine leukocidin gene, associated with community-acquired MRSA, was detected in 12 out of 27 potential MRSA samples. The femA gene was detected less frequently at beaches that met US enterococci criteria or EU enterococci 'excellent' recreational water quality, but was not related to Escherichia coli-defined criteria. Escherichia coli is often the only indicator used to determine water quality at US beaches, given the economic and healthcare burden that can be associated with infections caused by SA and MRSA, monitoring of recreational waters for non-fecal bacteria such as staphylococci and/or SA may be warranted.

Geographic setting influences Great Lakes beach microbiological water quality.

Understanding of factors that influence Escherichia coli (EC) and enterococci (ENT) concentrations, pathogen occurrence, and microbial sources at Great Lakes beaches comes largely from individual beach studies. Using 12 representative beaches, we tested enrichment cultures from 273 beach water and 22 tributary samples for EC, ENT, and genes indicating the bacterial pathogens Shiga-toxin producing E. coli (STEC), Shigella spp. , Salmonella spp , Campylobacter jejuni/coli , and methicillin-resistant Staphylococcus aureus , and 108-145 samples for Bacteroides human, ruminant, and gull source-marker genes. EC/ENT temporal patterns, general Bacteroides concentration, and pathogen types and occurrence were regionally consistent (up to 40 km), but beach catchment variables (drains/creeks, impervious surface, urban land cover) influenced exceedances of EC/ENT standards and detections of Salmonella and STEC. Pathogen detections were more numerous when the EC/ENT Beach Action Value (but not when the Geometric Mean and Statistical Threshold Value) was exceeded. EC, ENT, and pathogens were not necessarily influenced by the same variables. Multiple Bacteroides sources, varying by date, occurred at every beach. Study of multiple beaches in different geographic settings provided new insights on the contrasting influences of regional and local variables, and a broader-scale perspective, on significance of EC/ENT exceedances, bacterial sources, and pathogen occurrence.

Factors related to occurrence and distribution of selected bacterial and protozoan pathogens in Pennsylvania streams.

The occurrence and distribution of fecal indicator bacteria (FIB) and bacterial and protozoan pathogens are controlled by diverse factors. To investigate these factors in Pennsylvania streams, 217 samples were collected quarterly from a 27-station water-quality monitoring network from July 2007 through August 2009. Samples were analyzed for concentrations of Escherichia coli (EC) and enterococci (ENT) indicator bacteria, concentrations of Cryptosporidium oocysts and Giardia cysts, and the presence of four genes related to pathogenic types of EC (eaeA, stx2, stx1, rfb(O157)) plus three microbial source tracking (MST) gene markers that are also associated with pathogenic ENT and EC (esp, LTIIa, STII). Water samples were concurrently analyzed for basic water chemistry, physical measures of water quality, nutrients, metals, and a suite of 79 organic compounds that included hormones, pharmaceuticals, and antibiotics. For each sample location, stream discharge was measured by using standardized methods at the time of sample collection, and ancillary sample site information, such as land use and geological characteristics, was compiled. Samples exceeding recreational water quality criteria were more likely to contain all measured pathogen genes but not Cryptosporidium or Giardia (oo)cysts. FIB and Giardia density and frequency of eaeA gene occurrence were significantly related to season. When discharge at a sampling location was high (>75th percentile of daily mean discharge), there were greater densities of FIB and Giardia, and the stx2, rfb(O157), STII, and esp genes were found more frequently than at other discharge conditions. Giardia occurrence was likely related to nonpoint sources, which are highly influential during seasonal overland transport resulting from snowmelt and elevated precipitation in late winter and spring in Pennsylvania. When MST markers of human, swine, or bovine origin were present, samples more frequently carried the eaeA, stx2, stx1, and rfb(O157) genes, but no genes were related exclusively to an individual MST marker. The human source pharmaceuticals (HSPs) acetaminophen and caffeine were correlated with Giardia, and the presence of HSPs proved to be more useful than MST markers in distinguishing the occurrence of Giardia. The HSPs caffeine and carbamazepine were correlated with the sum total of pathogen genes detected in a sample, demonstrating the value of using HSPs as an indicator of fecally derived pathogens. Sites influenced by urban land use with less forest were more likely to have greater FIB and Giardia densities and sum of the array of pathogen genes. Sites dominated by shallow carbonate bedrock in the upstream catchment were likely to have greater FIB densities and higher sum totals of pathogen genes but no correlation with Giardia detection. Our study provides a range of specific environmental, chemical, geologic, and land-use variables related to occurrence and distribution of FIB and selected bacterial and protozoan pathogens in Pennsylvania streams. The information presented could be useful for resource managers in understanding bacterial and protozoan pathogen occurrence and their relation to fecal indicator bacteria in similar settings.