Search

Fecal pollution remains a significant challenge for recreational water quality management worldwide. In response, there is a growing interest in the use of real-time quantitative PCR (qPCR) methods to achieve same-day notification of recreational water quality and associated public health risk as well as to characterize fecal pollution sources for targeted mitigation. However, successful widespread implementation of these technologies requires the development of and access to a high-quality standard control material. Here, we report a single laboratory qPCR performance assessment of the National Institute of Standards and Technology Standard Reference Material 2917 (NIST SRM® 2917), a linearized plasmid DNA construct that functions with 13 recreational water quality qPCR assays. Performance experiments indicate the generation of standard curves with amplification efficiencies ranging from 0.95 ± 0.006 to 0.99 ± 0.008 and coefficient of determination values (R 2 ) ≥ 0.980. Regardless of qPCR assay, variability in repeated measurements at each dilution level were very low (quantification threshold standard deviations ≤ 0.657) and exhibited a heteroscedastic trend characteristic of qPCR standard curves. The influence of a yeast carrier tRNA added to the standard control material buffer was also investigated. Findings demonstrated that NIST SRM® 2917 functions with all qPCR methods and suggests that the future use of this control material by scientists and water quality managers should help reduce variability in concentration estimates and make results more consistent between laboratories., (Published by Elsevier Ltd.)

There is growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality management. The transition from a research tool to a standardized protocol requires a high degree of confidence in data quality across laboratories. Data quality is typically determined through a series of specifications that ensure good experimental practice and the absence of bias in the results due to DNA isolation and amplification interferences. However, there is currently a lack of consensus on how best to evaluate and interpret human fecal source identification qPCR experiments. This is, in part, due to the lack of standardized protocols and information on interlaboratory variability under conditions for data acceptance. The aim of this study is to provide users and reviewers with a complete series of conditions for data acceptance derived from a multiple laboratory data set using standardized procedures. To establish these benchmarks, data from HF183/BacR287 and HumM2 human-associated qPCR methods were generated across 14 laboratories. Each laboratory followed a standardized protocol utilizing the same lot of reference DNA materials, DNA isolation kits, amplification reagents, and test samples to generate comparable data. After removal of outliers, a nested analysis of variance (ANOVA) was used to establish proficiency metrics that include lab-to-lab, replicate testing within a lab, and random error for amplification inhibition and sample processing controls. Other data acceptance measurements included extraneous DNA contamination assessments (no-template and extraction blank controls) and calibration model performance (correlation coefficient, amplification efficiency, and lower limit of quantification). To demonstrate the implementation of the proposed standardized protocols and data acceptance criteria, comparable data from two additional laboratories were reviewed. The data acceptance criteria proposed in this study should help scientists, managers, reviewers, and the public evaluate the technical quality of future findings against an established benchmark., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Recent studies showing an association between fecal indicator organisms (FIOs) in sand and gastrointestinal (GI) illness among beachgoers with sand contact have important public health implications because of the large numbers of people who recreate at beaches and engage in sand contact activities. Yet, factors that influence fecal pollution in beach sand remain unclear. During the 2007 National Epidemiological and Environmental Assessment of Recreational (NEEAR) Water Study, sand samples were collected at three locations (60 m apart) on weekend days (Sat, Sun) and holidays between June and September at two marine beaches - Fairhope Beach, AL and Goddard Beach, RI - with nearby publicly-owned treatment works (POTWs) outfalls. F(+) coliphage, enterococci, Bacteroidales, fecal Bacteroides spp., and Clostridium spp. were measured in sand using culture and qPCR-based calibrator-cell equivalent methods. Water samples were also collected on the same days, times and transects as the 144 sand samples and were assayed using the same FIO measurements. Weather and environmental data were collected at the time of sample collection. Mean FIO concentrations in sand varied over time, but not space. Enterococci CFU and CCE densities in sand were not correlated, although other FIOs in sand were. The strongest correlation between FIO density in sand and water was fecal Bacteroides CCE, followed by enterococci CFU, Clostridium spp. CCE, and Bacteroidales CCE. Overall, the factors associated with FIO concentrations in sand were related to the sand-water interface (i.e., sand-wetting) and included daily average densities of FIOs in water, rainfall, and wave height. Targeted monitoring that focuses on daily trends of sand FIO variability, combined with information about specific water quality, weather, and environmental factors may inform beach monitoring and management decisions to reduce microbial burdens in beach sand. The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Gulls are often cited as important contributors of fecal contamination to surface waters, and some recreational beaches have used gull control measures to improve microbial water quality. In this study, gulls were chased from a Lake Michigan beach using specially trained dogs, and water quality improvements were quantified. Fecal indicator bacteria and potentially pathogenic bacteria were measured before and during gull control using culture methods and quantitative polymerase chain reaction (qPCR). Harassment by dogs was an effective method of gull control: average daily gull populations fell from 665 before to 17 during intervention; and a significant reduction in the density of a gull-associated marker was observed (p < 0.001). Enterococcus spp. and Escherichia coli densities were also significantly reduced during gull control (p < 0.001 and p = 0.012, respectively for culture methods; p = 0.012 and p = 0.034, respectively for qPCR). Linear regression results indicate that a 50% reduction in gulls was associated with a 38% and 29% decrease in Enterococcus spp. and E. coli densities, respectively. Potentially human pathogenic bacteria were detected on 64% of days prior to gull control and absent during gull intervention, a significant reduction (p = 0.005). This study demonstrates that gull removal can be a highly successful beach remedial action to improve microbial water quality.

The U.S. EPA has published recommendations for calibrator cell equivalent (CCE) densities of enterococci in recreational waters determined by a qPCR method in its 2012 recreational water quality criteria (RWQC). The CCE quantification unit stems from the calibration model used to estimate enterococci densities in recreational beach waters in the EPA National Epidemiological and Environmental Assessment of Recreational (NEEAR) Water Study and directly informed the derivation of the RWQC recommendations. Recent studies have demonstrated that CCE estimates from the method can vary when using different cultured Enterococcus cell preparations in calibrator samples. These differences have been attributed to differences in the quantities of targeted gene copies (target sequences) that are recovered per nominal calibrator cell by DNA extraction. Standardization of results from the calibration model will require the estimation of target sequence recoveries from the calibrator and water samples. In addition, comparisons of water sample results with the RWQC values will require a knowledge of target sequence recoveries from the NEEAR study calibrator samples. In this study recoveries of target sequences and the mean target sequence/cell ratio for the NEEAR study calibrator samples were retrospectively estimated with a corroborated standard curve. A modification of the calibration model was then used to estimate enterococci target sequence quantities in water samples from eight midwestern U.S. rivers. CCE estimates were obtained by dividing these target sequence quantities by the mean NEEAR study target sequence/cell ratio. This target sequence-based quantification approach resulted in a high degree of agreement in beach action decisions (determinations of whether bacterial fecal indicator densities are above or below RWQC-recommended values) from CCE results of the qPCR method and from culture dependent enumeration of both enterococci and Eschericia coli in the corresponding water samples. [ABSTRACT FROM AUTHOR]

The US Environmental Protection Agency has proposed the use of quantitative polymerase chain reaction (qPCR) as a rapid alternative analytical method for monitoring recreational water quality at beaches. For qPCR to be considered for other Clean Water Act purposes, such as inclusion in discharge permits and use in Total Maximum Daily Load calculations, it is necessary to understand how qPCR detectable genetic markers are influenced by wastewater disinfection. This study investigated genetic markers for Escherichia coli, Enterococcus, Clostridium spp., Bacteroides, total Bacteroidales, as well as the human-associated Bacteroides markers, HF183 and HumM2, to determine which, if any, were influenced by disinfection (chlorination or ultraviolet light) of effluents from secondary wastewater treatment in different seasons. The effects of disinfection on culturable enterococci, E. coli, Bacteroides, and C. perfringens were also compared to their associated genetic markers. Disinfection of secondary treatment effluents significantly reduced culturable fecal indicator bacteria (FIB) but not genetic marker densities. No significant differences were observed in the responses of FIB culture and genetic marker densities to type of disinfection (chlorination vs UV) or season. Results of this study provide evidence that qPCR may not be suitable for monitoring efficacy of wastewater disinfection on the inactivation of bacterial pathogens. [ABSTRACT FROM AUTHOR]

Abstract: A quantitative polymerase chain reaction (qPCR) method for the detection of enterococci fecal indicator bacteria has been shown to be generally applicable for the analysis of temperate fresh (Great Lakes) and marine coastal waters and for providing risk-based determinations of water quality at recreational beaches. In this study we further examined the applicability of the method for analyses of diverse inland waters as well as tropical marine waters from Puerto Rico based on the frequencies of samples showing presumptive PCR interference. Interference was assessed by salmon DNA sample processing control (SPC) and internal amplification control (IAC) assay analysis results and pre-established acceptance criteria of <3.0 and <1.5 cycle threshold (Ct) offsets from control samples, respectively. SPC assay results were accepted in analyses of 93% of the inland water samples whereas the criterion was met at frequencies of 60% and 97% in analyses of samples from Puerto Rico in two different years of sampling. The functionality of the control assays and their acceptance criteria was assessed on the basis of relative recovery estimates of spiked enterococci target organisms extracted in the presence of water sample filters and sample-free control filters and was supported by observations that recovery estimates from the water sample and control filters were substantially different for samples that failed these criteria. Through the combined use of the SPC and IAC assays, two presumptive types of interference were identified. One type, observed in the tropical marine water samples, appeared to primarily affect the availability of the DNA templates for detection. The second type, observed in river water samples, appeared to primarily affect PCR amplification efficiency. In the presence of DNA template interference, adjustments from SPC assay results by the ΔΔCt comparative Ct calculation method decreased the variability of spiked enterococci recovery estimates and increased the similarity with control filters as compared to unadjusted recovery estimates obtained by the ΔCt calculation method. Use of a higher salmon DNA concentration in the extraction buffer also reduced this type of interference. The effects of amplification interference were largely reversed by dilution of the DNA extracts and even more effectively by the use of an alternative, commercial PCR reagent, designed for the analysis of environmental samples. [Copyright &y& Elsevier]

Fecal pollution remains a challenge for water quality managers at Great Lakes and inland recreational beaches. The fecal indicator of choice at these beaches is typically Escherichia coli (E. coli), determined by culture-based methods that require over 18 h to obtain results. Researchers at the United States Environmental Protection Agency (EPA) have developed a rapid E. coli qPCR methodology (EPA Draft Method C) that can provide same-day results for improving public health protection with demonstrated sensitivity, specificity, and data acceptance criteria. However, limited information is currently available to compare the occurrence of E. coli determined by cultivation and by EPA Draft Method C (Method C). This study provides a large-scale data collection effort to compare the occurrence of E. coli determined by these alternative methods at more than 100 Michigan recreational beach and other sites using the complete set of quantitative data pairings and selected subsets of the data and sites meeting various eligibility requirements. Simple linear regression analyses of composite (pooled) data indicated a correlation between results of the E. coli monitoring approaches for each of the multi-site datasets as evidenced by Pearson R-squared values ranging from 0.452 to 0.641. Theoretical Method C threshold values, expressed as mean log10 target gene copies per reaction, that corresponded to an established E. coli culture method water quality standard of 300 MPN or CFU /100 mL varied only from 1.817 to 1.908 for the different datasets using this model. Different modeling and derivation approaches that incorporated within and between-site variability in the estimates also gave Method C threshold values in this range but only when relatively well-correlated datasets were used to minimize the error. A hypothetical exercise to evaluate the frequency of water impairments based on theoretical qPCR thresholds corresponding to the E. coli water quality standard for culture methods suggested that the methods may provide the same beach notification outcomes over 90% of the time with Method C results differing from culture method results that indicated acceptable and unacceptable water quality at overall rates of 1.9% and 6.6%, respectively. Results from this study provide useful information about the relationships between E. coli determined by culture and qPCR methods across many diverse freshwater sites and should facilitate efforts to implement qPCR-based E. coli detection for rapid recreational water quality monitoring on a large scale in the State of Michigan. • A rapid E. coli qPCR method can provide same-day results for beach monitoring. • A large study compared the occurrence of E. coli by qPCR and culture in Michigan. • Results provide an indication of the degree of correlation between the methods. • Options for a beach notification threshold value for the PCR method are presented. [ABSTRACT FROM AUTHOR]

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 log 10 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. Image 1 • Variability in E. coli gene copy estimates from an EPA qPCR method was assessed. • Alternative calibration models affected variability but not overall mean estimates. • Failures to meet proposed data quality acceptance criteria excluded 24% of analyses. • Outlier gene copy estimates were not always associated with criteria failures. • Lab experience and their handling of control materials affected method performance. [ABSTRACT FROM AUTHOR]

Abstract: Enterococci target sequence density estimates from analyses of diluted river water DNA extracts by EPA Methods 1611 and 1609 and estimates with lower detection limits from undiluted DNA extracts by Method 1609 were indistinguishable. These methods should be equally suitable for comparison with U.S. EPA 2012 Recreational Water Quality Criteria values. [Copyright &y& Elsevier]

Abstract: Quantitative polymerase chain reaction (qPCR) is increasingly being used for the quantitative detection of fecal indicator bacteria in beach water. QPCR allows for same-day health warnings, and its application is being considered as an option for recreational water quality testing in the United States (USEPA, 2011. EPA-OW-2011-0466, FRL-9609-3, Notice of Availability of Draft Recreational Water Quality Criteria and Request for Scientific Views). However, transition of qPCR from a research tool to routine water quality testing requires information on how various method variations affect target enumeration. Here we compared qPCR performance and enumeration of enterococci in spiked and environmental water samples using three qPCR platforms (Applied Biosystem StepOnePlus™, the BioRad iQ™5 and the Cepheid SmartCycler® II), two reference materials (lyophilized cells and frozen cells on filters) and two comparative CT quantification models (ΔCT and ΔΔCT). Reference materials exerted the biggest influence, consistently affecting results by approximately 0.5 log10 unit. Platform had the smallest effect, generally exerting <0.1 log10 unit difference in final results. Quantification model led to small differences (0.04–0.2 log10 unit) in this study with relatively uninhibited samples, but has the potential to cause as much as 8-fold (0.9 log10 unit) difference in potentially inhibitory samples. Our findings indicate the need for a certified and centralized source of reference materials and additional studies to assess applicability of the quantification models in analyses of PCR inhibitory samples. [Copyright &y& Elsevier]

Abstract: Background: Traditional fecal indicator bacteria (FIB) measurement is too slow (>18 h) for timely swimmer warnings. Objectives: Assess relationship of rapid indicator methods (qPCR) to illness at a marine beach impacted by urban runoff. Methods: We measured baseline and two-week health in 9525 individuals visiting Doheny Beach 2007–08. Illness rates were compared (swimmers vs. non-swimmers). FIB measured by traditional (Enterococcus spp. by EPA Method 1600 or Enterolert™, fecal coliforms, total coliforms) and three rapid qPCR assays for Enterococcus spp. (Taqman, Scorpion-1, Scorpion-2) were compared to health. Primary bacterial source was a creek flowing untreated into ocean; the creek did not reach the ocean when a sand berm formed. This provided a natural experiment for examining FIB-health relationships under varying conditions. Results: We observed significant increases in diarrhea (OR 1.90, 95% CI 1.29–2.80 for swallowing water) and other outcomes in swimmers compared to non-swimmers. Exposure (body immersion, head immersion, swallowed water) was associated with increasing risk of gastrointestinal illness (GI). Daily GI incidence patterns were different: swimmers (2-day peak) and non-swimmers (no peak). With berm-open, we observed associations between GI and traditional and rapid methods for Enterococcus; fewer associations occurred when berm status was not considered. Conclusions: We found increased risk of GI at this urban runoff beach. When FIB source flowed freely (berm-open), several traditional and rapid indicators were related to illness. When FIB source was weak (berm-closed) fewer illness associations were seen. These different relationships under different conditions at a single beach demonstrate the difficulties using these indicators to predict health risk. [Copyright &y& Elsevier]