Validity assessment of Michigan's proposed qPCR threshold value for rapid water-quality monitoring of E. coli contamination.

Michigan's water-quality standards specify that E. coli concentrations at bathing beaches must not exceed 300 E. coli per 100 mL, as determined by the geometric mean of culture-based concentrations in three or more representative samples from a given beach on a given day. Culture-based analysis requires 18⁠-⁠24 h to complete, so results are not available on the day of sampling. This one-day delay is problematic because results cannot be used to prevent recreation at beaches that are unsafe on the sampling day, nor do they reliably indicate whether recreation should be prevented the next day, due to high between-day variability in E. coli concentrations demonstrated by previous studies. By contrast, qPCR-based E. coli concentrations can be obtained in 3-4 h, making same-day beach notification decisions possible. Michigan has proposed a qPCR threshold value (qTV) for E. coli of 1.863 log10 gene copies per reaction as a potential equivalent value to the state standard, based on statistical analysis of a set of state-wide training data from 2016 to 2018. The main purpose of the present study is to assess the validity of the proposed qTV by determining whether the implied qPCR-based beach notification decisions agree well with culture-based decisions on two sets of test data from 2016⁠-⁠2018 (6,564 samples) and 2019-2020 (3,205 samples), and whether performance of the proposed qTV is similar on the test and training data. The results show that performance of Michigan's proposed qTV on both sets of test data was consistently good (e.g., 95% agreement with culture-based beach notification decisions during 2019⁠-⁠2020) and was as good as or better than its performance on the training data set. The false-negative rate for the proposed qTV was 25-29%, meaning that beach notification decisions based on the qTV would be expected to permit recreation on the day of sampling in 25-29% of cases where the beach exceeds the state standard for FIB contamination. This false-negative rate is higher than one would hope to see but is well below the corresponding error rate for culture-based decisions, which permit recreation at beaches that exceed the state standard on the day of sampling in 100% of cases because of the one-day delay in obtaining results. The key advantage of qPCR-based analysis is that it permits a large percentage (71-75%) of unsafe beaches to be identified in time to prevent recreation on the day of sampling.

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.

The impact of environmental parameters on microcystin production in dialysis bag experiments.

It is important to understand what environmental parameters may regulate microcystin (MC) production and congener type. To determine if environmental conditions in two hydraulically connected lakes can influence MC production and congener ratios, we incubated dialysis bags containing phytoplankton from mesotrophic/eutrophic Muskegon Lake into hypereutrophic Bear Lake (Michigan, USA) and vice versa. Strong cyanobacteria growth was observed in all dialysis bags with Bear Lake phytoplankton in July and August. Phytoplankton communities were dominated by Aphanizomenon aphanizomenoides, Microcystis wesenbergii, Limnothrix redekei. MC concentrations were correlated with M. wesenbergii and A. aphanizomenoides biovolume. MC concentrations in bags incubated in the Muskegon Lake with Bear Lake water were significantly higher than the other bags. The higher light intensity and total nitrogen concentration may have caused the increase of MC production. The MC-LR/MC-RR ratios varied with sample origin but not with lake of incubation, indicating that physical environmental factors (water temperature and turbidity) were not the reasons for different toxin production ratios. Differences in total phosphorus concentrations might be one reason for the dissimilarity of the MC-LR/MC-RR ratio between the two lakes. The higher light intensity and NO3-N concentration in Muskegon Lake are two factors contributing to an increase of MC production.

Landfill cover soil, soil solution, and vegetation responses to municipal landfill leachate applications.

Municipal solid waste landfill leachate must be removed and treated to maintain landfill cover integrity and to prevent contamination of surface and ground waters. From 2003 to 2007, we studied an onsite disposal system in Ottawa County, Michigan, where leachate was spray irrigated on the vegetated landfill cover. We established six 20-m-diameter circular experimental plots on the landfill; three were spray irrigated as part of the operational system, and three remained as untreated control plots. We quantified the effects of leachate application on soil properties, soil solution chemistry, vegetative growth, and estimated solute leaching. The leachate had high mean levels of electrical conductivity (0.6-0.7 S m(-1)), Cl (760-900 mg L(-1)), and NH(4)-N (290-390 mg L(-1)) but was low in metals and volatile organic compounds. High rates of leachate application in 2003 (32 cm) increased soil electrical conductivity and NO(3)-N leaching, so a sequential rotation of spray areas was implemented to limit total leachate application to <9.6 cm yr(-1) per spray area. Concentrations of NO(3)-N and leaching losses remained higher on irrigated plots in subsequent years but were substantially reduced by spray area rotation. Leachate irrigation increased plant biomass but did not significantly affect soil metal concentrations, and plant metal concentrations remained within normal ranges. Rotating spray areas and timing irrigation to conform to seasonal capacities for evapotranspiration reduced the localized impacts of leachate application observed in 2003. Careful monitoring of undiluted leachate applications is required to avoid adverse impacts to vegetation or soils and elevated solute leaching losses.