Search

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.

Municipal stormwater systems are designed to collect, transport, and discharge precipitation from a defined catchment area into local surface waters. However, these discharges may contain unsafe levels of fecal waste. Paired measurements of Escherichia coli, precipitation, three land use metrics determined by geographic information system (GIS) mapping, and host-associated genetic markers indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), dog (DG3), and avian (GFD) fecal sources were assessed in 231 urban stream samples impacted by two or more municipal stormwater outfalls. Receiving water samples were collected twice per month (n = 24) and after rain events (n = 9) from seven headwaters of the Anacostia River in the District of Columbia (United States) exhibiting a gradient of impervious surface, residential, and park surface areas. Almost 50% of stream samples (n = 103) were impaired, exceeding the local E. coli single sample maximum assessment level (410 MPN/100 ml). Fecal scores (average log10 copies per 100 ml) were determined to prioritize sites by pollution source and to evaluate potential links with land use, rainfall, and E. coli levels using a recently developed censored data analysis approach. Dog, ruminant, and avian fecal scores were almost always significantly increased after rain or when E. coli levels exceeded the local benchmark. Human fecal pollution trends showed the greatest variability with detections ranging from 9.1% to 96.7% across sites. Avian fecal scores exhibited the closest connection to land use, significantly increasing in catchments with larger residential areas after rain events (p = 0.038; R2 = 0.62). Overall, results demonstrate that combining genetic fecal source identification methods with GIS mapping complements routine E. coli monitoring to improve management of urban streams impacted by stormwater outfalls. [ABSTRACT FROM AUTHOR]

A major challenge for society in the 21st century will be replacement, design, and optimal management of urban infrastructure. It is estimated that the current worldwide demand for infrastructure investment is approximately three trillion dollars annually. A Drinking Water Infrastructure Needs Survey conducted by the U.S. Environmental Protection Agency estimated that community water systems nationwide have an immediate need of $12.1 billion in infrastructure investment, primarily to protect against microbiological contamination. This paper presents equations that can be used to estimate the cost of system construction, expansion, and rehabilitation and repair for distribution system components. Equations have been developed for installation of new pipe, trenching, embedment, and the other unit operations that are required to replace or construct new distribution system components. Equations have also been developed to estimate the cost of cement mortar lining, sliplining, and corrosion control. These equations can be used in an additive manner to estimate the cost of all of the unit operations required for replacing or laying new distribution system piping, and for a limited set of rehabilitation and repair options. CE Database keywords: Water supply; Costs; Water distribution; Rehabilitation; Regression models; Pipes.

There is growing concern over the need to rehabilitate, replace, and repair drinking water distribution systems and wastewater collection systems in the United States. A recent survey conducted by the U.S. Environmental Protection Agency found that $138 billion will be needed to maintain and replace existing drinking water systems over the next 20 years. It is estimated that $77 billion of this expenditure will be dedicated to repairing and rehabilitating pipelines. Given the cost and disruption caused by replacing distribution system pipe using conventional open trench technology, utilities are beginning to increase the application of rehabilitation or trenchless replacement technologies to extend the life of existing pipes. This paper discusses the various types of technologies that can be used for rehabilitation and repair of drinking water distribution components. It also presents representative costs that can be used by utility managers to estimate order-of-magnitude budgetary costs for rehabilitation and replacement of distribution system components. DOI: 10.1061/(ASCE)0733-9496(2002)128:4(303) CE Database keywords: Water distribution; Costs; Pipes; Rehabilitation; Excavation; Trenching; Replacement.

A major objective of drinking water treatment is to provide water that is both microbiologically and chemically safe for human consumption. Drinking water chlorination, therefore, poses a dilemma. Chemical disinfection reduces the risk of infectious disease, but the interaction between chemical disinfectants and precursor materials in source water may result in potentially harmful by-products. Chlorine consumption results in the formation of by-products, and the loss of chlorine residual reduces protection against potentially pathogenic bacteria. Therefore, much effort has been invested in characterizing the loss of chlorine residuals in raw and treated water. This paper presents a mathematical model based on the use of two second-order terms for predicting this loss or decay. DOI: 10.1061/(ASCE)0733-9496(2002)128:2(152) CE Database keywords: Pottable water; Chlorine; Mathematical models; Prediction.

Chlorination is the most widely practiced form of disinfection in the United States. It is highly effective against most microbiological contaminants. However, there is concern that the disinfection by-products (DBPs) formed by the use of chlorine might be carcinogenic. One class of DBPs that are formed and the only class of DBPs that currently are regulated are total trihalomethanes (TTHMs). Therefore, much effort is being expended in developing models that can be used to predict both TTHMs and chlorine residual levels in treated drinking water. This paper presents a model that predicts both TTHMs and chlorine residuals based on the consumption of chlorine and can be used to assist in evaluating the complex balance between microbial and DBP risks associated with disinfecting drinking water with chlorine. The parameters of the model have been found to be functions of total organic carbon, pH, temperature, and initial chlorine residual level. Bromide and the subsequent formation of brominated by-products were not considered in this paper.

To determine resistance of highly pathogenic avian influenza (H5N1) virus to chlorination, we exposed allantoic fluid containing 2 virus strains to chlorinated buffer at pH 7 and 8, at 5[degrees]C. [...]

Abstract 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.

A performance evaluation of seven end-point PCR and real-time quantitative PCR (qPCR) assays which are associated with either ruminant or bovine feces are reported. The large discrepancies in the performance of bovine-associated assays across different bovine populations and variability in assay performance between host populations indicated that the use of bovine microbial source-tracking applications would need a prior characterization at each water-shed of interest.

The quantitative PCR arrays are developed for the quantification of two human-specific genetic markers targeting Bacteriodales-like cell surface-associated genes. Assay performance combined with the prevalence of DNA targets in sewage samples have provided evidence that has supported the application of these quantitative methods for monitoring fecal pollution in ambient environmental waters.

Quantitative PCR assays are developed for the detection of bovine feces-specific genetic markers and a method is designed for the enumeration of these markers by using a Markov chain Monte Carlo approach. Acceptable assay performance combined with the prevalence of DNA targets across different cattle populations have shown that these quantitative assays are useful in monitoring bovine fecal pollution in ambient waters.

Fecal pollution management remains one of the biggest challenges for water quality authorities worldwide. Advanced fecal pollution source identification technologies are now available that can provide quantitative information from many animal groups. As public interest in these methodologies grows, it is vital to use standardized procedures with clearly defined data acceptance metrics and conduct field studies demonstrating the use of these techniques to help resolve real-world water quality challenges. Here we apply recently standardized human-associated qPCR methods with custom data acceptance metrics (HF183/BacR287 and HumM2), along with established procedures for ruminant (Rum2Bac), cattle (CowM2 and CowM3), canine (DG3 and DG37), and avian (GFD) fecal pollution sources to (i) demonstrate the feasibility of implementing standardized qPCR procedures in a large-scale field study, and (ii) characterize trends in fecal pollution sources in the research area. A total of 602 water samples were collected over a one-year period at 29 sites along the Trask, Kilchis, and Tillamook rivers and tributaries in the Tillamook Bay Watershed (OR, USA). Host-associated qPCR results were combined with high-resolution geographic information system (GIS) land use and general indicator bacteria (E. coli) measurements to elucidate water quality fecal pollution trends. Results demonstrate the feasibility of implementing standardized fecal source identification qPCR methods with established data acceptance metrics in a large-scale field study leading to new investigative leads suggesting that elevated E. coli levels may be linked to specific pollution sources and land use activities in the Tillamook Bay Watershed. [ABSTRACT FROM AUTHOR]

Although disinfection was one of the major public health advances in the last century and continues to be so in the twenty-first century, the disinfectants themselves may react with naturally occurring materials in treated water to form unintended by-products, which may themselves pose risks. This is of particular concern with regard to the use of chlorine. Generation of disinfection by-products (DBPs) has been shown to be a function of various factors including total organic carbon concentration, type of organic precursor, chlorination level, pH, temperature, reaction time, and UV-254 absorbance. Another factor affecting DBP formation is the presence and concentration of the bromide ion in the raw or finished water. Bromine substitutes for chlorine to produce bromine-containing homologues of the more familiar chlorine species. The current list of by-products targeted for regulation contains brominated and mixed bromine-chlorine species of total trihalomethanes and haloacetic acids. These are known to form in bromide-containing waters when chlorinated. To control chlorination DBPs therefore requires an understanding of the factors that influence their formation. This paper presents a model that can be used to predict the formation of chlorinated, brominated, and mixed species compounds based on initial chlorine concentration, chlorine consumption, bromide ion concentration, and pH. The model clearly shows that higher levels of bromide in the water favor the formation of brominated compounds. Brominated compounds also form faster than chlorinated compounds.

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]

There is a growing interest for the use of coliphage as an alternative indicator to assess fecal pollution in recreational waters. Coliphage are a group of viruses that infect Escherichia coli and are considered as potential surrogates to infer the likely presence of enteric viral pathogens. We report the use of a dead-end hollow fiber ultrafiltration single agar layer method to enumerate F+ and somatic coliphage from surface waters collected from three Great Lake areas. At each location, three sites (two beaches; one river) were sampled five days a week over the 2015 beach season (n = 609 total samples). In addition, culturable E. coli and enterococci concentrations, as well as 16 water quality and recreational area parameters were assessed such as rainfall, turbidity, dissolved oxygen, pH, and ultra violet absorbance. Overall, somatic coliphage levels ranged from non-detectable to 4.39 log 10 plaque forming units per liter and were consistently higher compared to F+ (non-detectable to 3.15 log 10  PFU/L), regardless of sampling site. Coliphage concentrations weakly correlated with cultivated fecal indicator bacteria levels ( E. coli and enterococci) at 75% of beach sites tested in study (r = 0.28 to 0.40). In addition, ultraviolet light absorption and water temperature were closely associated with coliphage concentrations, but not fecal indicator bacteria levels suggesting different persistence trends in Great Lake waters between indicator types (bacteria versus virus). Finally, implications for coliphage water quality management and future research directions are discussed. [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]

Abstract: 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 4×104 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 (>103 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. [Copyright &y& Elsevier]

Two bacteriophages, ϕ6 and ϕ8, were investigated as potential surrogates for H5N1 highly pathogenic avian influenza virus in persistence and chlorine inactivation studies in water. In the persistence studies, ϕ6 and ϕ8 remained infectious at least as long as the H5N1 viruses at both 17 and 28°C in fresh water, but results varied in salinated water. The bacteriophage ϕ6 also exhibited a slightly higher chlorine resistance than that of the H5N1 viruses. Based upon these findings, the bacteriophages may have potential for use as surrogates in persistence and inactivation studies in fresh water. [ABSTRACT FROM AUTHOR]

Adverse health effects that may result from chronic exposure to mixtures of disinfection by-products (DBPs) present in drinking waters may be linked to both the types and concentrations of DBPs present. Depending on the characteristics of the source water and treatment processes used, both types and concentrations of DBPs found in drinking waters vary substantially. The composition of a drinking-water mixture also may change during distribution. This study evaluated the relationships between mutagenicity, using the Ames assay, and water quality parameters. The study included information on treatment, mutagenicity data, and water quality data for source waters, finished waters, and distribution samples collected from five full-scale drinking water treatment plants, which used chlorine exclusively for disinfection. Four of the plants used surface water sources and the fifth plant used groundwater. Correlations between mutagenicity and water quality parameters are presented. The highest correlation was observed between mutagenicity and the total organic halide concentrations in the treated samples. [ABSTRACT FROM AUTHOR]

The objective of this study was to measure hydroxyl radical reaction rates using both UV/H[sub2]O[sub2] and pulse radiolysis techniques for 10 US EPA Contaminant Candidate List compounds (2,6- and 2,4-DNT, EPTC, prometon, linuron, diuron, RDX, molinate, nitrobenzene, and terbacil). The rate constants determined using these techniques were compared to each other and to values reported in the literature. Difference factors between k[subOH] obtained using UV/H[sub2]O[sub2] and pulse radiolysis ranged from 1.1 to 4.7. It was shown that even small differences in hydroxyl radical rate constants values can result in fairly large differences (up to 50%) when trying to predict removals of pollutants in an advanced oxidation process. [ABSTRACT FROM AUTHOR]

Because lot variability is accounted for in the current Long Term 2 Enhanced Surface Water Treatment Rule, water utilities may want to use a similar safety factor for a sequential inactivation process to inactivate C. parvum oocysts with ozone. [ABSTRACT FROM AUTHOR]

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]

Numerous studies have demonstrated the efficiency of ultraviolet (UV) radiation for the inactivation of oocysts of Cryptosporidium parvum. in these studies inactivation is measured as reduction in oocysts. A primary goal is to estimate the UV radiation required to achieve a high degree of inactivation. Different lots of Cryptosporidium parvum oocysts are used in these studies, and the inactivation rate may vary depending on the lot of oocysts used. The goal of this paper is to account for the error in estimating the amount of inactivation after exposure to UV radiation, and for the effect of lot variability in determining the required UV radiation. A Bayesian approach is used to simultaneously model the logistic dose-response model and the UV inactivation kinetic model. The oocysts lot variability is incorporated using a hierarchical Bayesian model. Posterior distributions using Markov Chain Monte Carlo method is used to obtain estimates and Bayesian credible interval for the required UV radiation to achieve a given inactivation level of Cryptosporidium parvum oocysts. [ABSTRACT FROM AUTHOR]