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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]

Introduction: In the United States and elsewhere, recreational water quality is monitored for fecal indicator bacteria to help prevent swimming-associated illnesses. Standard methods to measure these bacteria take at least 24 hours to obtain results. Molecular approaches such as quantitative polymerase chain reaction (qPCR) can estimate these bacteria faster, in under 3 hours. Previously, we demonstrated that measurements of the fecal indicator bacteria Enterococcus using qPCR were associated with gastrointestinal (GI) illness among swimmers at freshwater beaches. In this paper, we report on results from three marine beach sites. Methods: We interviewed beach-goers and collected water samples at marine beaches affected by treated sewage discharges in Mississippi in 2005, and Rhode Island and Alabama in 2007. Ten to twelve days later, we obtained information about gastrointestinal, respiratory, eye, ear and skin symptoms by telephone. We tested water samples for fecal indicator organisms using qPCR and other methods. Results: We enrolled 6,350 beach-goers. The occurrence of GI illness among swimmers was associated with a log10-increase in exposure to qPCR-determined estimates of fecal indicator organisms in the genus Enterococcus (AOR = 2.6, 95% CI 1.3-5.1) and order Bacteroidales (AOR = 1.9, 95% CI 1.3-2.9). Estimates of organisms related to Clostridium perfringens and a subgroup of organisms in the genus Bacteroides were also determined by qPCR in 2007, as was F+ coliphage, but relationships between these indicators and illness were not statistically significant. Conclusions: This study provides the first evidence of a relationship between gastrointestinal illness and estimates of fecal indicator organisms determined by qPCR at marine beaches. [ABSTRACT FROM AUTHOR]

The article presents a study that investigates the use of Environmental Relative Moldiness Index (ERMI) in diagnosing childhood respiratory disorders and monitor exposure in the U.S. As part of the Housing and Urban Development's American Healthy Homes Survey, dust samples were collected from a nationally representative homes in the U.S. using the Mitest sampler. Five milligrams of sieved dust was analyzed by mold-specific quantitative polymerase chain reaction for the 36 indicator species in 1096 samples. The researchers concluded that the Environmental Relative Moldiness Index scale may be useful for home mold-burden estimates in epidemiological studies particularly on the said illness.

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]

Very little is known about the density and distribution of fecal indicator bacteria (FIB) genetic markers measured by quantitative real-time PCR (qPCR) in fecal pollution sources. Before qPCR-based FIB technologies can be applied to waste management and public health risk applications, it is vital to characterize the concentrations of these genetic markers in pollution sources (i.e., untreated wastewater and animal feces). We report the distribution of rRNA genetic markers for several general FIB groups, including Clostridium spp., Escherichia coli, enterococci, and Bacteroidales, as determined by qPCR on reference collections consisting of 54 primary influent sewage samples collected from treatment facilities across the United States and fecal samples representing 20 different animal species. Based on raw sewage sample collection data, individual FIB genetic markers exhibited a remarkable similarity in concentration estimates from locations across the United States ranging from Hawaii to Florida. However, there was no significant correlation between genetic markers for most FIB combinations (P > 0.05). In addition, large differences (up to 5 log10 copies) in the abundance of FIB genetic markers were observed between animal species, emphasizing the importance of indicator microorganism selection and animal source contribution for future FIB applications. [ABSTRACT FROM AUTHOR]

The quantitative polymerase chain reaction (qPCR) method provides rapid estimates of fecal indicator bacteria densities that have been indicated to be useful in the assessment of water quality. Primarily because this method provides faster results than standard culture-based methods, the U.S. Environmental Protection Agency is currently considering its use as a basis for revised ambient water quality criteria. In anticipation of this possibility, we sought to examine the relationship between qPCR-based and culture-based estimates of enterococci in surface waters. Using data from several research groups, we compared enterococci estimates by the two methods in water samples collected from 37 sites across the United States. A consistent linear pattern in the relationship between cell equivalents (CCE), based on the qPCR method, and colony-forming units (CFU), based on the traditional culturable method, was significant (P < 0.05) at most sites. A linearly decreasing variance of CCE with increasing CFU levels was significant (P < 0.05) or evident for all sites. Both marine and freshwater sites under continuous influence of point-source contamination tended to reveal a relatively constant proportion of CCE to CFU. The consistency in the mean and variance patterns of CCE versus CFU indicates that the relationship of results based on these two methods is more predictable at high CFU levels (e.g., log10CFU > 2.0/100 mL) while uncertainty increases at lower CFU values. It was further noted that the relative error in replicated qPCR estimates was generally higher than that in replicated culture counts even at relatively high target levels, suggesting a greater need for replicated analyses in the qPCR method to reduce relative error. Further studies evaluating the relationship between culture and qPCR should take into account analytical uncertainty as well as potential differences in results of these methods that may arise from sample variability, different sources of pollution, and environmental factors. [ABSTRACT FROM AUTHOR]

Fungal concentrations were measured in the dust of 6 homes in Cleveland, Ohio, where an infant developed pulmonary hemorrhage (pulmonary hemorrhage homes [PHH]) and 26 reference homes (RH) with no known fungal contamination. Quantitative polymerase chain reaction assays for 82 species (or assay groups) were used to identify and quantify fungal concentrations. The ratios of the geometric means of PHH to RH were > 1 for 26 species (group I). However, the same ratios were <1 for 10 species (group II). Probit analysis of the sum of the logs of the concentrations of these 2 groups resulted in a 95% probability range for separating PHH from RH homes. The same 82 fungal species were also tested for hemolysin production on sheep's blood agar (incubated at 37°C). Hemolysins were more commonly produced by group I species (42%) compared with group II species (10%). [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AR) is a serious global problem due to the overuse of antimicrobials in human, animal, and agriculture sectors. There is intense research to control the dissemination of AR, but little is known regarding the environmental drivers influencing its spread. Although AR genes (ARGs) are detected in many different environments, the risk associated with the spread of these genes to microbial pathogens is unknown. Recreational microbial exposure risks are likely to be greater in water bodies receiving discharge from human and animal waste in comparison to less disturbed aquatic environments. Given this scenario, research practitioners are encouraged to consider an ecological context to assess the effect of environmental ARGs on public health. Here, we use a stratified, probabilistic survey of nearly 2000 sites to determine national patterns of the anthropogenic indicator class I integron Integrase gene ( intI1 ) and several ARGs in 1.2 million kilometers of United States (US) rivers and streams. Gene concentrations were greater in eastern than in western regions and in rivers and streams in poor condition. These first of their kind findings on the national distribution of intI1 and ARGs provide new information to aid risk assessment and implement mitigation strategies to protect public health.

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.)

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., (Published by Elsevier B.V.)

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 total of 65 quantitative PCR (QPCR) assays, incorporating fluorigenic 5' nuclease (TaqMan) chemistry and directed at the nuclear ribosomal RNA operon, internal transcribed spacer regions (ITS1 or ITS2) was developed and tested for the detection of selected Aspergillus, Penicillium and Paecilomyces species. The assays varied in specificity from species or subspecies to closely related species groups, subject to the amount of nucleotide sequence variation in the different organisms. A generic assay for all target species of Aspergillus, Penicillium and Paecilomyces was also developed and tested. Using a previously reported DNA extraction method, estimated conidia detection limits for target species ranged from less than one to several hundred per sample for the different assays. Conidia detection limits for non-target species were at least 1,000 fold higher in nearly all instances. The assays were used to analyze ten HVAC dust samples from different sources around the US. Total quantities of Aspergillus, Penicillium and Paecilomyces conidia in the samples, determined by the generic assay and the summed totals from the specific assays, were in general agreement, suggesting that all of the numerically dominant species in the samples were accounted for by the specific assays. QPCR analyses of these samples after spiking them with selected target organisms indicated that the enumeration results were within approximately a one-half log range of the expected values 95% of the time. Evidence is provided that the commonly used practices of enumerating Aspergillus and Penicillium as a single group or only by genus can be misleading in understanding the indoor populations of these organisms and their potential health risks.