Search

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., (Published by Elsevier B.V.)

The State of California has mandated the preparation of a guidance document on the application of fecal source identification methods for recreational water quality management. California contains the fifth highest population of cattle in the United States, making the inclusion of cow-associated methods a logical choice. Because the performance of these methods has been shown to change based on geography and/or local animal feeding practices, laboratory comparisons are needed to determine which assays are best suited for implementation. We describe the performance characterization of two end-point PCR assays (CF128 and CF193) and five real-time quantitative PCR (qPCR) assays (Rum2Bac, BacR, BacCow, CowM2, and CowM3) reported to be associated with either ruminant or cattle feces. Each assay was tested against a blinded set of 38 reference challenge filters (19 duplicate samples) containing fecal pollution from 12 different sources suspected to impact water quality. The abundance of each host-associated genetic marker was measured for qPCR-based assays in both target and non-target animals and compared to quantities of total DNA mass, wet mass of fecal material, as well as Bacteroidales, and enterococci determined by 16S rRNA qPCR and culture-based approaches (enterococci only). Ruminant- and cow-associated genetic markers were detected in all filters containing a cattle fecal source. However, some assays cross-reacted with non-target pollution sources. A large amount of variability was evident across laboratories when protocols were not fixed suggesting that protocol standardization will be necessary for widespread implementation. Finally, performance metrics indicate that the cattle-associated CowM2 qPCR method combined with either the BacR or Rum2Bac ruminant-associated methods are most suitable for implementation., (Published by Elsevier Ltd.)

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 log(10) unit. Platform had the smallest effect, generally exerting <0.1 log(10) unit difference in final results. Quantification model led to small differences (0.04-0.2 log(10) unit) in this study with relatively uninhibited samples, but has the potential to cause as much as 8-fold (0.9 log(10) 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 © 2012 Elsevier Ltd. All rights reserved.)

Molecular methods for quantifying defined Bacteroidales species from the human gastrointestinal tract may have important clinical and environmental applications, ranging from diagnosis of infections to fecal source tracking in surface waters. In this study, sequences from the V2 region of the small subunit ribosomal RNA gene were targeted in the development of qPCR assays to quantify DNA from six Bacteroides and one Prevotella species. In silico and experimental analyses suggested that each of the assays was highly discriminatory in detecting DNA from the intended species. Analytical sensitivity, precision and ranges of quantification were demonstrated for each assay by coefficients of variation of less than 2% for cycle threshold measurements over a range from 10 to 4×10(4) target sequence copies. The assays were applied to assess the occurrence and relative abundance of their target sequences in feces from humans and five animal groups as well as in 14 sewage samples from 13 different treatment facilities. Sequences from each of the species were detected at high levels (>10(3)copies/ng total extracted DNA) in human wastes. Sequences were also detected by each assay in all sewage samples and, with exception of the Prevotella sequences, showed highly correlated (R(2)≥0.7) variations in concentrations between samples. In contrast, the occurrence and relative abundance profiles of these sequences differed substantially in the fecal samples from each of the animal groups. These results suggest that analyses for multiple individual Bacteroidales species may be useful in identifying human fecal pollution in environmental waters., (Published by Elsevier GmbH.)

Real-time PCR absolute quantification applications are becoming more common in the recreational and drinking water quality industries. Many methods rely on the use of standard curves to make estimates of DNA target concentrations in unknown samples. Traditional absolute quantification approaches dictate that a standard curve must accompany each experimental run. However, the generation of a standard curve for each qPCR experiment set-up can be expensive and time consuming, especially for studies with large numbers of unknown samples. As a result, many researchers have adopted a master calibration strategy where a single curve is derived from DNA standard measurements generated from multiple instrument runs. However, a master curve can inflate uncertainty associated with intercept and slope parameters and decrease the accuracy of unknown sample DNA target concentration estimates. Here we report two alternative strategies termed 'pooled' and 'mixed' for the generation of calibration equations from absolute standard curves which can help reduce the cost and time of laboratory testing, as well as the uncertainty in calibration model parameter estimates. In this study, four different strategies for generating calibration models were compared based on a series of repeated experiments for two different qPCR assays using a Monte Carlo Markov Chain method. The hierarchical Bayesian approach allowed for the comparison of uncertainty in intercept and slope model parameters and the optimization of experiment design. Data suggests that the 'pooled' model can reduce uncertainty in both slope and intercept parameter estimates compared to the traditional single curve approach. In addition, the 'mixed' model achieved uncertainty estimates similar to the 'single' model while increasing the number of available reaction wells per instrument run., (Published by Elsevier Ltd.)

There are numerous PCR-based assays available to characterize human fecal pollution in ambient waters. Each assay employs distinct oligonucleotides and many target different genes and microorganisms leading to potential variations in assay performance. Performance comparisons utilizing feces and raw sewage samples are needed to determine which assays are best suited for expensive and time-consuming field validation, fate, transport, and epidemiology studies. We report the assessment of five end-point PCR and 10 real-time quantitative PCR (qPCR) assays that target genes from presumptive Bacteroidales microorganisms reported to be associated with human feces. Each assay was tested against a reference collection of 54 primary influent sewage samples collected from different geographical locations across the United States and 174 fecal DNA extracts from 23 different animal sources. Experiments indicate that human-associated genetic markers are distributed across a broad range of human populations but show substantial differences in specificity for human feces suggesting that particular assays may be more suitable than others depending on the abundance of genetic marker required for detection and the animal sources impacting a particular watershed or beach of interest.

There are numerous PCR-based assays available to characterize bovine fecal pollution in ambient waters. The determination of which approaches are most suitable for field applications can be difficult because each assay targets a different gene, in many cases from different microorganisms, leading to variation in assay performance. We describe a performance evaluation of seven end-point PCR and real-time quantitative PCR (qPCR) assays reported to be associated with either ruminant or bovine feces. Each assay was tested against a reference collection of DNA extracts from 247 individual bovine fecal samples representing 11 different populations and 175 fecal DNA extracts from 24 different animal species. Bovine-associated genetic markers were broadly distributed among individual bovine samples ranging from 39 to 93%. Specificity levels of the assays spanned 47.4% to 100%. End-point PCR sensitivity also varied between assays and among different bovine populations. For qPCR assays, the abundance of each host-associated genetic marker was measured within each bovine population and compared to results of a qPCR assay targeting 16S rRNA gene sequences from Bacteroidales. Experiments indicate large discrepancies in the performance of bovine-associated assays across different bovine populations. Variability in assay performance between host populations suggests that the use of bovine microbial source-tracking applications will require a priori characterization at each watershed of interest.

Assessment of health risk and fecal bacterial loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantification approach. We report the development of quantitative PCR assays for quantification of two recently described human-specific genetic markers targeting Bacteroidales-like cell surface-associated genes. Each assay exhibited a range of quantification from 10 to 1 x 10(6) copies of target DNA. For each assay, internal amplification controls were developed to detect the presence or absence of amplification inhibitors. The assays predominantly detected human fecal specimens and exhibited specificity levels greater than 97% when tested against 265 fecal DNA extracts from 22 different animal species. The abundance of each human-specific genetic marker in primary effluent wastewater samples collected from 20 geographically distinct locations was measured and compared to quantities estimated by real-time PCR assays specific for rRNA gene sequences from total Bacteroidales and enterococcal fecal microorganisms. Assay performances combined with the prevalence of DNA targets in sewage samples provide experimental evidence supporting the potential application of these quantitative methods for monitoring fecal pollution in ambient environmental waters.

Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described bovine feces-specific genetic markers and a method for the enumeration of these markers using a Markov chain Monte Carlo approach. Both assays exhibited a range of quantification from 25 to 2 x 10(6) copies of target DNA, with a coefficient of variation of <2.1%. One of these assays can be multiplexed with an internal amplification control to simultaneously detect the bovine-specific genetic target and presence of amplification inhibitors. The assays detected only cattle fecal specimens when tested against 204 fecal DNA extracts from 16 different animal species and also demonstrated a broad distribution among individual bovine samples (98 to 100%) collected from five geographically distinct locations. The abundance of each bovine-specific genetic marker was measured in 48 individual samples and compared to quantitative PCR-enumerated quantities of rRNA gene sequences representing total Bacteroidetes, Bacteroides thetaiotaomicron, and enterococci in the same specimens. Acceptable assay performance combined with the prevalence of DNA targets across different cattle populations provides experimental evidence that these quantitative assays will be useful in monitoring bovine fecal pollution in ambient waters.

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. Image 1 • Data QA criteria were established for an EPA E. coli qPCR method (Draft Method C). • QA parameters were slope, intercept for standard curve, LLOQ, Ct values of controls. • Data QA was based on use of prescribed reference and control materials by 21 labs. • The study also provides guidance for labs to establish QA with their own materials. • Polymerase reagent lots should be checked for E. coli signal before use in Method C. [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 An obstacle to establishing widely useful data acceptance criteria for U.S. Environmental Protection Agency (EPA) qPCR methods has been the unavailability of standardized reference materials. Earlier versions of EPA Methods 1609 and 1611 for enterococci used cellular reference materials for quantifying enterococci in unknown test samples, however, EPA updates to these fundamentally DNA-based analysis methods have shifted toward the use of DNA standards. This report describes the application of droplet digital PCR (ddPCR) analysis for the quantification of a set of synthetic plasmid DNA standards that have been made available for updated EPA Methods 1609.1 and 1611.1 as well as for EPA Draft Method C for Escherichia coli. To obtain the most accurate concentration estimates possible, part of this effort was to develop a data analysis model for determining the fluorescence thresholds that distinguish positive from negative droplets produced by the ddPCR reactions. Versions of this model are described for applications with individual reactions, multiple reactions within a ddPCR system run, and multiple reactions within and across different system runs. The latter version was applied toward determinations of error in the concentration estimates of the standards from replicate analyses of each standard in multiple ddPCR system runs. Mean concentration estimates for the five standards from the ddPCR analyses were 4.356, 3.381, 2.371, 1.641 and 1.071 log 10 copies/5 μL with associated standard deviations of 0.074, 0.082, 0.108, 0.131 and 0.188, respectively. These estimates contrasted with expected log 10 concentrations of 4.6, 3.6, 2.6, 1.9 and 1.3 copies/5 μL, respectively, based on the yield of the plasmid reported by the vendor and spectrophotometric analysis of the initial stock solution of this material. These results illustrate how the analyses of original stocks may lead to potential bias(es) in the concentration estimates of final DNA standards and subsequently in the estimates of unknown test samples determined from these standards in qPCR analyses. Highlights • Plasmid DNA standards were prepared as reference materials for EPA qPCR methods. • The main basis of standards quantification was droplet digital PCR (ddPCR) analysis. • Instrument software & a novel Mixture Model were used to identify positive droplets. • Error estimates from the Mixture Model were used to assess standards stability. • Results illustrate the value of quantifying actual standards over undiluted stocks. [ABSTRACT FROM AUTHOR]

Human fecal pollution of recreational waters remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality research and management. However, there are currently no standardized approaches for field implementation and interpretation of qPCR data. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and a novel Bayesian weighted average approach to establish a human fecal contamination score (HFS) that can be used to prioritize sampling sites for remediation based on measured human waste levels. The HFS was then used to investigate 975 study design scenarios utilizing different combinations of sites with varying sampling intensities (daily to once per week) and number of qPCR replicates per sample (2–14 replicates). Findings demonstrate that site prioritization with HFS is feasible and that both sampling intensity and number of qPCR replicates influence reliability of HFS estimates. The novel data analysis strategy presented here provides a prescribed approach for the implementation and interpretation of human-associated HF183/BacR287 qPCR data with the goal of site prioritization based on human fecal pollution levels. In addition, information is provided for future users to customize study designs for optimal HFS performance. [ABSTRACT FROM AUTHOR]

The application of quantitative real-time PCR (qPCR) technologies for the rapid identification of fecal bacteria in environmental waters is being considered for use as a national water quality metric in the United States. The transition from research tool to a standardized protocol requires information on the reproducibility and sources of variation associated with qPCR methodology across laboratories. This study examines interlaboratory variability in the measurement of enterococci and Bacteroidales concentrations from standardized, spiked, and environmental sources of DNA using the Entero1a and GenBac3 qPCR methods, respectively. Comparisons are based on data generated from eight different research facilities. Special attention was placed on the influence of the DNA isolation step and effect of simplex and multiplex amplification approaches on interlaboratory variability. Results suggest that a crude lysate is sufficient for DNA isolation unless environmental samples contain substances that can inhibit qPCR amplification. No appreciable difference was observed between simplex and multiplex amplification approaches. Overall, interlaboratory variability levels remained low (<10% coefficient of variation) regardless of qPCR protocol. [ABSTRACT FROM AUTHOR]

Abstract: DNA extracts from enumerated target organism cells (calibrator samples) have been used for estimating Enterococcus cell equivalent densities in surface waters by a comparative cycle threshold (Ct) qPCR analysis method. To compare surface water Enterococcus density estimates from different studies by this approach, either a consistent source of calibrator cells must be used or the estimates must account for any differences in target sequence recoveries from different sources of calibrator cells. In this report we describe two methods for estimating target sequence recoveries from whole cell calibrator samples based on qPCR analyses of their serially diluted DNA extracts and most probable number (MPN) calculation. The first method employed a traditional MPN calculation approach. The second method employed a Bayesian hierarchical statistical modeling approach and a Monte Carlo Markov Chain (MCMC) simulation method to account for the uncertainty in these estimates associated with different individual samples of the cell preparations, different dilutions of the DNA extracts and different qPCR analytical runs. The two methods were applied to estimate mean target sequence recoveries per cell from two different lots of a commercially available source of enumerated Enterococcus cell preparations. The mean target sequence recovery estimates (and standard errors) per cell from Lot A and B cell preparations by the Bayesian method were 22.73 (3.4) and 11.76 (2.4), respectively, when the data were adjusted for potential false positive results. Means were similar for the traditional MPN approach which cannot comparably assess uncertainty in the estimates. Cell numbers and estimates of recoverable target sequences in calibrator samples prepared from the two cell sources were also used to estimate cell equivalent and target sequence quantities recovered from surface water samples in a comparative Ct method. Our results illustrate the utility of the Bayesian method in accounting for uncertainty, the high degree of precision attainable by the MPN approach and the need to account for the differences in target sequence recoveries from different calibrator sample cell sources when they are used in the comparative Ct method. [Copyright &y& Elsevier]

Background: In real-time quantitative PCR studies using absolute plasmid DNA standards, a calibration curve is developed to estimate an unknown DNA concentration. However, potential differences in the amplification performance of plasmid DNA compared to genomic DNA standards are often ignored in calibration calculations and in some cases impossible to characterize. A flexible statistical method that can account for uncertainty between plasmid and genomic DNA targets, replicate testing, and experiment-to-experiment variability is needed to estimate calibration curve parameters such as intercept and slope. Here we report the use of a Bayesian approach to generate calibration curves for the enumeration of target DNA from genomic DNA samples using absolute plasmid DNA standards. Results: Instead of the two traditional methods (classical and inverse), a Monte Carlo Markov Chain (MCMC) estimation was used to generate single, master, and modified calibration curves. The mean and the percentiles of the posterior distribution were used as point and interval estimates of unknown parameters such as intercepts, slopes and DNA concentrations. The software WinBUGS was used to perform all simulations and to generate the posterior distributions of all the unknown parameters of interest. Conclusion: The Bayesian approach defined in this study allowed for the estimation of DNA concentrations from environmental samples using absolute standard curves generated by real-time qPCR. The approach accounted for uncertainty from multiple sources such as experiment-to-experiment variation, variability between replicate measurements, as well as uncertainty introduced when employing calibration curves generated from absolute plasmid DNA standards. [ABSTRACT FROM AUTHOR]

Draft method C is a standardized method for quantifying E. coli densities in recreational waters using quantitative polymerase chain reaction (qPCR). The method includes a Microsoft Excel workbook that automatically screens for poor-quality data using a set of previously proposed acceptance criteria, generates weighted linear regression (WLR) composite standard curves, and calculates E. coli target gene copies in test samples. We compared standard curve parameter values and test sample results calculated with the WLR model to those from a Bayesian master standard curve (MSC) model using data from a previous multi-lab study. The two models' mean intercept and slope estimates from twenty labs' standard curves were within each other's 95% credible or confidence intervals for all labs. E. coli gene copy estimates of six water samples analyzed by eight labs were highly overlapping among labs when quantified with the WLR and MSC models. Finally, we compared multiple labs' 2016–2018 composite curves, comprised of data from individual curves where acceptance criteria were not used, to their corresponding composite curves with passing acceptance criteria. Composite curves developed from passing individual curves had intercept and slope 95% confidence intervals that were often narrower than without screening and an analysis of covariance test was passed more often. The Excel workbook WLR calculation and acceptance criteria will help laboratories implement draft method C for recreational water analysis in an efficient, cost-effective, and reliable manner. [ABSTRACT FROM AUTHOR]

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 (notemplate 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. [ABSTRACT FROM AUTHOR]

Quantitative polymerase chain reaction (qPCR) has become a frequently used technique for quantifying enterococci in recreational surface waters, but there are several methodological options. Here we evaluated how three method permutations, type of mastermix, sample extract dilution and use of controls in results calculation, affect method reliability among multiple laboratories with respect to sample interference. Multiple samples from each of 22 sites representing an array of habitat types were analyzed using EPA Method 1611 and 1609 reagents with full strength and five-fold diluted extracts. The presence of interference was assessed three ways: using sample processing and PCR amplifications controls; consistency of results across extract dilutions; and relative recovery of target genes from spiked enterococci in water sample compared to control matrices with acceptable recovery defined as 50 to 200%. Method 1609, which is based on an environmental mastermix, was found to be superior to Method 1611, which is based on a universal mastermix. Method 1611 had over a 40% control assay failure rate with undiluted extracts and a 6% failure rate with diluted extracts. Method 1609 failed in only 11% and 3% of undiluted and diluted extracts analyses. Use of sample processing control assay results in the delta–delta Ct method for calculating relative target gene recoveries increased the number of acceptable recovery results. Delta–delta tended to bias recoveries from apparent partially inhibitory samples on the high side which could help in avoiding potential underestimates of enterococci — an important consideration in a public health context. Control assay and delta–delta recovery results were largely consistent across the range of habitats sampled, and among laboratories. The methodological option that best balanced acceptable estimated target gene recoveries with method sensitivity and avoidance of underestimated enterococci densities was Method 1609 without extract dilution and using the delta–delta calculation method. The applicability of this method can be extended by the analysis of diluted extracts to sites where interference is indicated but, particularly in these instances, should be confirmed by augmenting the control assays with analyses for target gene recoveries from spiked target organisms. [ABSTRACT FROM AUTHOR]

Urban runoff can carry a variety of pollutants into recreational beaches, often including bacterial pathogens and indicators of fecal contamination. To develop complete recreational criteria and risk assessments, it is necessary to understand conditions under which human contamination could be present at beaches solely impacted by urban runoff. Accurately estimating risk requires understanding sources, concentrations, and transport mechanisms of microbial contaminants in these environments. By applying microbial source tracking methods and empirical modeling, we assessed the presence and level of human contamination at urban runoff impacted recreational beaches. We also identified environmental parameters and pollution sources that can influence the concentration and transport of culturable and molecular fecal indicator bacteria (FIB) in systems impacted solely by urban runoff. Water samples and physico–chemical parameters were collected from shoreline locations from three South Carolina (SC) beaches (five locations per beach) and two Florida (FL) beaches (three locations per beach). Each SC beach was directly impacted by swashes or tidal creeks receiving stormwater runoff from the urbanized area and therefore were designated as swash drain associated (SDA) beaches, while FL beaches were designated as non-swash drain associated (NSDA). Sampling in swash drains (SD; three sites per SD) directly impacting each SC beach was also conducted. Results indicate that although culturable (enterococci ) and real-time quantitative polymerase chain reaction (qPCR) (EC23S857, Entero1, and GenBac3) FIB concentrations were, on average, higher at SD locations, SDA beaches did not have consistently higher molecular FIB signals compared to NSDA beaches. Both human-associated markers (HF183 and HumM2) were concomitantly found only at SDA beaches. Bacteroidales species-specific qPCR markers (BsteriF1 and BuniF2) identified differences in the Bacteroidales community, depending on beach type. The marker for general Bacteroidales was most abundant at SD locations and exhibited a high correlation with both culturable and other molecular markers. Combining molecular information with predictive modeling allowed us to identify both alongshore movement of currents and SD outflow as significant influences on the concentration of molecular and culturable indicators in the bathing zone. Data also suggests that combining methodologies is a useful and cost effective approach to help understand transport dynamics of fecal contamination and identify potential sources of contamination at marine beaches. [ABSTRACT FROM AUTHOR]

Quantitative real-time PCR (qPCR) assays that target the human-associated HF183 bacterial cluster within members of the genus Bacteroides are among the most widely used methods for the characterization of human fecal pollution in ambient surface waters. In this study, we show that a current TaqMan HF183 qPCR assay (HF183/BFDrev) routinely forms nonspecific amplification products and introduce a modified TaqMan assay (HF183/BacR287) that alleviates this problem. The performance of each qPCR assay was compared in head-to-head experiments investigating limits of detection, analytical precision, predicted hybridization to 16S rRNA gene sequences from a reference database, and relative marker concentrations in fecal and sewage samples. The performance of the modified HF183/BacR287 assay is equal to or improves upon that of the original HF183/BFDrev assay. In addition, a qPCR chemistry designed to combat amplification inhibition and a multiplexed internal amplification control are included. In light of the expanding use of PCR-based methods that rely on the detection of extremely low concentrations of DNA template, such as qPCR and digital PCR, the new TaqMan HF183/BacR287 assay should provide more accurate estimations of human-derived fecal contaminants in ambient surface waters. [ABSTRACT FROM AUTHOR]

Calves make up about 16% of the current bovine population in the United States and can excrete high levels of human pathogens in their feces. We describe the density and distribution of genetic markers from 9 PCR- and real-time quantitative PCR-based assays, including CF128, CF193, CowM2, CowM3, GenBac3, Entero1, EC23S857, CampF2, and ttr-6, commonly used to help assess ambient surface water quality. Each assay was tested against a collection of 381 individual bovine fecal samples representing 31 mother and calf pairings collected over a 10-month time period from time of birth through weaning. Genetic markers reported to be associated with ruminant and/or bovine fecal pollution were virtually undetected in calves for up to 115 days from birth, suggesting that physiological changes in calf ruminant function impact host-associated genetic marker shedding. In addition, general fecal indicator markers for Bacteroidales, Escherichia coli, and Enterococcus spp. exhibited three separate trends across time, indicating that these bacteria respond differently to age-related physiological and dietary changes during calf development. The results of this study suggest that currently available PCR-based water quality indicator technologies can under- or overestimate fecal pollution originating from calves and identify a need for novel calf-associated source identification methods. [ABSTRACT FROM AUTHOR]

Abstract: The characteristics of fecal sources, and the ways in which they are measured, can profoundly influence the interpretation of which sources are contaminating a body of water. Although feces from various hosts are known to differ in mass and composition, it is not well understood how those differences compare across fecal sources and how differences depend on characterization methods. This study investigated how nine different fecal characterization methods provide different measures of fecal concentration in water, and how results varied across twelve different fecal pollution sources. Sources investigated included chicken, cow, deer, dog, goose, gull, horse, human, pig, pigeon, septage and sewage. A composite fecal slurry was prepared for each source by mixing feces from 6 to 22 individual samples with artificial freshwater. Fecal concentrations were estimated by physical (wet fecal mass added and total DNA mass extracted), culture-based (Escherichia coli and enterococci by membrane filtration and defined substrate), and quantitative real-time PCR (Bacteroidales, E. coli, and enterococci) characterization methods. The characteristics of each composite fecal slurry and the relationships between physical, culture-based and qPCR-based characteristics varied within and among different fecal sources. An in silico exercise was performed to assess how different characterization methods can impact identification of the dominant fecal pollution source in a mixed source sample. A comparison of simulated 10:90 mixtures based on enterococci by defined substrate predicted a source reversal in 27% of all possible combinations, while mixtures based on E. coli membrane filtration resulted in a reversal 29% of the time. This potential for disagreement in minor or dominant source identification based on different methods of measurement represents an important challenge for water quality managers and researchers. [Copyright &y& Elsevier]

Diffuse sources of human fecal pollution allow for the direct discharge of waste into receiving waters with minimal or no treatment. Traditional culture-based methods are commonly used to characterize fecal pollution in ambient waters, however these methods do not discern between human and other animal sources of fecal pollution making it difficult to identify diffuse pollution sources. Human-associated quantitative real-time PCR (qPCR) methods in combination with low-order headwatershed sampling, precipitation information, and high-resolution geographic information system land use data can be useful for identifying diffuse source of human fecal pollution in receiving waters. To test this assertion, this study monitored nine headwatersheds over a two-year period potentially impacted by faulty septic systems and leaky sanitary sewer lines. Human fecal pollution was measured using three different human-associated qPCR methods and a positive significant correlation was seen between abundance of human-associated genetic markers and septic systems following wet weather events. In contrast, a negative correlation was observed with sanitary sewer line densities suggesting septic systems are the predominant diffuse source of human fecal pollution in the study area. These results demonstrate the advantages of combining water sampling, climate information, land-use computer-based modeling, and molecular biology disciplines to better characterize diffuse sources of human fecal pollution in environmental waters. [ABSTRACT FROM AUTHOR]