Occurrence of recreational water quality monitoring general fecal indicator bacteria and fecal source identification genetic markers in gray seal scat

The number of gray seals (Halichoerus grypus) observed along the United States Northwest Atlantic region has been increasing for decades. These colonial animals often haul-out on beaches seasonally in numbers ranging from a few individuals to several thousands. While these larger aggregations are an important part of gray seal behavior, there is public concern that haul-outs could lead to large amounts of fecal waste in recreational areas, potentially resulting in beach closures. Yet, data to confirm whether these animals contribute to beach closures is lacking and minimal information is available on the occurrence of key water quality monitoring genetic markers in gray seal scat. This study evaluates the concentration of E. coli (EC23S857), enterococci (Entero1a), and fecal Bacteroidetes (GenBac3) as well as six fecal source identification genetic markers (HF183/BacR287, HumM2, CPQ_056, Rum2Bac, DG3, and GFD) measured by qPCR in 48 wild gray seal scat samples collected from two haul-out areas in Cape Cod (Massachusetts, U.S.A.). Findings indicate that FIB genetic markers are shed in gray seal scat at significantly different concentrations with the Entero1a genetic marker exhibiting the lowest average concentration (-0.73 log10 estimated mean copies per nanogram of DNA). In addition, systematic testing of scat samples demonstrated that qPCR assays targeting host-associated genetic markers indicative of human, ruminant, and canine fecal pollution sources remain highly specific in waters frequented by gray seals (>97 % specificity).

A fecal score approximation model for analysis of real-time quantitative PCR fecal source identification measurements

Numerous qPCR-based methods are available to estimate the concentration of fecal pollution sources in surface waters. However, qPCR fecal source identification data sets often include a high proportion of non-detections (reactions failing to attain a prespecified minimal signal intensity for detection) and measurements below the assay lower limit of quantification (minimal signal intensity required to estimate target concentration), making it challenging to interpret results in a quantitative manner while accounting for error. In response, a Bayesian statistic based Fecal Score (FS) approach was developed that estimates the weighted average concentration of a fecal source identification genetic marker across a defined group of samples, mathematically incorporating qPCR measurements from all samples. Yet, implementation is technically demanding and computationally intensive requiring specialized training, the use of expert software, and access to high performance computing. To address these limitations, this study reports a novel approximation model for FS determination based on a frequentist approach. The performance of the Bayesian and Frequentist models are compared using fecal source identification qPCR data representative of different 'censored' data scenarios from a recently published study focusing on the impact of stormwater discharge in urban streams. In addition, data set eligibility recommendations for the responsible use of these models are presented. Findings indicate that the Frequentist model can generate similar average concentrations and uncertainty estimates for FS, compared to the original Bayesian approach. The Frequentist model should make calculations less computationally and technically intensive, allowing for the development of easier to use data analysis tools for fecal source identification applications.

Have genetic targets for faecal pollution diagnostics and source tracking revolutionised water quality analysis yet?

The impacts on faecal pollution analysis using nucleic acid-based methods, such as PCR and sequencing, in health-related water quality research were assessed by rigorous literature analysis. A wide range of application areas and study designs has been identified since the first application more than 30 years ago (>1,100 publications). Given the consistency of methods and assessment types, we suggest defining this emerging part of science as a new discipline: genetic faecal pollution diagnostics (GFPD) in health-related microbial water quality analysis. Undoubtedly, GFPD has already revolutionised faecal pollution detection and microbial source tracking, the current core applications. GFPD is also expanding to many other research areas, including infection and health risk assessment, evaluation of microbial water treatment, and support of wastewater surveillance. In addition, storage of DNA extracts allows for biobanking, which opens up new perspectives. The tools of GFPD can be combined with cultivation-based standardised faecal indicator enumeration, pathogen detection, and various environmental data types, in an integrated data analysis approach. This comprehensive meta-analysis provides the scientific status quo of this field, including trend analyses and literature statistics, outlining identified application areas, and discussing the benefits and challenges of nucleic acid-based analysis in GFPD.

Genetic fecal source identification in urban streams impacted by municipal separate storm sewer system discharges

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.

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

Bacterial and viral fecal indicator predictive modeling at three Great Lakes recreational beach sites

Coliphage are viruses that infect Escherichia coli (E. coli) and may indicate the presence of enteric viral pathogens in recreational waters. There is an increasing interest in using these viruses for water quality monitoring and forecasting; however, the ability to use statistical models to predict the concentrations of coliphage, as often done for cultured fecal indicator bacteria (FIB) such as enterococci and E. coli, has not been widely assessed. The same can be said for FIB genetic markers measured using quantitative polymerase chain reaction (qPCR) methods. Here we institute least-angle regression (LARS) modeling of previously published concentrations of cultured FIB (E. coli, enterococci) and coliphage (F+, somatic), along with newly reported genetic concentrations measured via qPCR for E. coli, enterococci, and general Bacteroidales. We develop site-specific models from measures taken at three beach sites on the Great Lakes (Grant Park, South Milwaukee, WI; Edgewater Beach, Cleveland, OH; Washington Park, Michigan City, IN) to investigate the efficacy of a statistical predictive modeling approach. Microbial indicator concentrations were measured in composite water samples collected five days per week over a beach season (∼15 weeks). Model predictive performance (cross-validated standardized root mean squared error of prediction [SRMSEP] and R2PRED) were examined for seven microbial indicators (using log10 concentrations) and water/beach parameters collected concurrently with water samples. Highest predictive performance was seen for qPCR-based enterococci and Bacteroidales models, with F+ coliphage consistently yielding poor performing models. Influential covariates varied by microbial indicator and site. Antecedent rainfall, bird abundance, wave height, and wind speed/direction were most influential across all models. Findings suggest that some fecal indicators may be more suitable for water quality forecasting than others at Great Lakes beaches.

Effectiveness of two wastewater disinfection strategies for the removal of fecal indicator bacteria, bacteriophage, and enteric viral pathogens concentrated using dead-end hollow fiber ultrafiltration (D-HFUF)

Primary influent and final effluent samples were collected from wastewater treatment plants using either chlorination or ultraviolet (UV) disinfection biweekly for one year. Paired measurements were determined for fecal indicator bacteria (Escherichia coli and enterococci), cultivated bacteriophages (somatic, F+, and CB-390 coliphage and GB-124 Bacteroides phage), human-associated viral markers (human polyomavirus [HPyV] and crAssphage), enteric pathogens (adenovirus, noroviruses genogroups I and II) as well as total infectious enteric virus. To increase the probability of detecting low concentration targets, both primary (10L) and final effluent wastewater samples (40-100 L) were concentrated using a dead-end hollow-fiber ultrafilter (D-HFUF). Despite seasonal temperature fluctuations, concentration shifts of FIB, bacteriophages, human-associated viruses, and viral pathogens measured in primary influent samples were minimal, while levels of infectious enteric virus were significantly higher in the spring and fall (P range: 0.0003-0.0409). FIB levels measured in primary influents were 1-2 log₁₀ higher than bacteriophage, human-associated viral markers (except crAssphage) and viral pathogens measured. FIB displayed the greatest sensitivity to chlorine disinfection, while crAssphage, adenoviruses and infectious enteric viruses were significantly less sensitive (P ≤ 0.0096). During UV treatment, bacteriophages F+ and GB-124 were the most resistant of the culturable viruses measured (P ≤ 0.001), while crAssphage were the most resistant (P ≤ 0.0124) overall. When UV lamps were inactive, infectious enteric viruses were significantly more resilient to upstream treatment processes than all other targets measured (P ≤ 0.0257). Similar to infectious enteric viruses and adenoviruses; GB-124, F+, and crAssphages displayed the highest resistance to UV irradiation, signaling a potential applicability as pathogen surrogates in these systems. The use of D-HFUF enhanced the ability to estimate removal of viruses through wastewater treatment, with the expectation that future applications of this method will be used to better elucidate viral behavior within these systems.

Performance of NIST SRM® 2917 with 13 recreational water quality monitoring qPCR assays

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 (R2) ≥ 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.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Variability in RT-qPCR assay parameters indicates unreliable SARS-CoV-2 RNA quantification for wastewater surveillance

Due to the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has become an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. In particular, reverse transcription-quantitative PCR (RT-qPCR) has been used to generate large datasets aimed at detecting and quantifying SARS-CoV-2 RNA in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method yet, there are no certified quantification standards, and experiments are conducted using different assays, reagents, instruments, and data analysis protocols. These variations can induce errors in quantitative data reports, thereby potentially misleading interpretations, and conclusions. We review the SARS-CoV-2 wastewater surveillance literature focusing on variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices, as described in the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a frequent lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

Variability in RT-qPCR assay parameters indicates unreliable SARS-CoV-2 RNA quantification for wastewater surveillance

Due to the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has become an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. In particular, reverse transcription-quantitative PCR (RT-qPCR) has been used to generate large datasets aimed at detecting and quantifying SARS-CoV-2 RNA in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method yet, there are no certified quantification standards, and experiments are conducted using different assays, reagents, instruments, and data analysis protocols. These variations can induce errors in quantitative data reports, thereby potentially misleading interpretations, and conclusions. We review the SARS-CoV-2 wastewater surveillance literature focusing on variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices, as described in the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a frequent lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

Variable fecal source prioritization in recreational waters routinely monitored with viral and bacterial general indicators

Somatic and F+ coliphage methods are under consideration as potential routine surface water quality monitoring tools to identify unsafe levels of fecal pollution in recreational waters. However, little is known about the cooccurrence of these virus-based fecal indicators and host-associated genetic markers used to prioritize key pollution sources for remediation. In this study, paired measurements of cultivated coliphage (somatic and F+) and bacterial (E. coli and enterococci) general fecal indicators and genetic markers indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), canine (DG3), and avian (GFD) fecal pollution sources were assessed in 365 water samples collected from six Great Lakes Basin beach and river sites over a 15-week recreational season. Water samples were organized into groups based on defined viral and bacterial fecal indicator water quality thresholds and average log10 host-associated genetic marker fecal score ratios were estimated to compare pollutant source inferences based on variable routine water quality monitoring practices. Eligible log10 fecal score ratios ranged from -0.051 (F+ coliphage, GFD) to 2.08 (enterococci, Rum2Bac). Using a fecal score ratio approach, findings suggest that general fecal indicator selection for routine water quality monitoring can influence the interpretation of host-associated genetic marker measurements, in some cases, prioritizing different pollutant sources for remediation. Variable trends were also observed between Great Lake beach and river sites suggesting disparate management practices may be useful for each water type.

Metagenomic Sequencing and Quantitative Real-Time PCR for Fecal Pollution Assessment in an Urban Watershed

Microbial contamination of recreation waters is a major concern globally, with pollutants originating from many sources, including human and other animal wastes often introduced during storm events. Fecal contamination is traditionally monitored by employing culture methods targeting fecal indicator bacteria (FIB), namely E. coli and enterococci, which provides only limited information of a few microbial taxa and no information on their sources. Host-associated qPCR and metagenomic DNA sequencing are complementary methods for FIB monitoring that can provide enhanced understanding of microbial communities and sources of fecal pollution. Whole metagenome sequencing (WMS), quantitative real-time PCR (qPCR), and culture-based FIB tests were performed in an urban watershed before and after a rainfall event to determine the feasibility and application of employing a multi-assay approach for examining microbial content of ambient source waters. Cultivated E. coli and enterococci enumeration confirmed presence of fecal contamination in all samples exceeding local single sample recreational water quality thresholds (E. coli, 410 MPN/100 mL; enterococci, 107 MPN/100 mL) following a rainfall. Test results obtained with qPCR showed concentrations of E. coli, enterococci, and human-associated genetic markers increased after rainfall by 1.52-, 1.26-, and 1.11-fold log₁₀ copies per 100 mL, respectively. Taxonomic analysis of the surface water microbiome and detection of antibiotic resistance genes, general FIB, and human-associated microorganisms were also employed. Results showed that fecal contamination from multiple sources (human, avian, dog, and ruminant), as well as FIB, enteric microorganisms, and antibiotic resistance genes increased demonstrably after a storm event. In summary, the addition of qPCR and WMS to traditional surrogate techniques may provide enhanced characterization and improved understanding of microbial pollution sources in ambient waters.

Identifying septic pollution exposure routes during a waterborne norovirus outbreak - A new application for human-associated microbial source tracking qPCR

In June 2017, the Pennsylvania Department of Health (PADOH) was notified of multiple norovirus outbreaks associated with 179 ill individuals who attended separate events held at an outdoor venue and campground over a month period. Epidemiologic investigations were unable to identify a single exposure route and therefore unable to determine whether there was a persistent contamination source to target for exposure mitigation. Norovirus was detected in a fresh recreational water designated swimming area and a drinking water well. A hydrogeological site evaluation suggested a nearby septic leach field as a potential contamination source via ground water infiltration. Geological characterization revealed a steep dip of the bedrock beneath the septic leach field toward the well, providing a viral transport pathway in a geologic medium not previously documented as high risk for viral ground water contamination. The human-associated microbial source tracking (MST) genetic marker, HF183, was used as a microbial tracer to demonstrate the hydrogeological connection between the malfunctioning septic system, drinking water well, and recreational water area. Based on environmental investigation findings, venue management and local public health officials implemented a series of outbreak prevention strategies including discontinuing the use of the contaminated well, issuing a permit for a new drinking water well, increasing portable toilet and handwashing station availability, and promoting proper hand hygiene. Despite the outbreaks at the venue and evidence of ground water contamination impacting nearby recreational water and the drinking water well, no new norovirus cases were reported during a large event one week after implementing prevention practices. This investigation highlights a new application for human-associated MST methods to trace hydrological connections between multiple fecal pollutant exposure routes in an outbreak scenario. In turn, pollutant source information can be used to develop effective intervention practices to mitigate exposure and prevent future outbreaks associated with human fecal contaminated waters.

Contamination Scenario Matters when Using Viral and Bacterial Human-Associated Genetic Markers as Indicators of a Health Risk in Untreated Sewage-Impacted Recreational Waters

Fecal pollution at beaches can pose a health risk to recreators. Quantitative microbial risk assessment (QMRA) is a tool to evaluate the use of candidate fecal indicators to signify a health risk from enteric pathogens in sewage-impacted waters. We extend the QMRA approach to model mixtures of sewage at different ages using genetic marker concentrations for human-associated crAssphage, Bacteroides spp., and polyomavirus in sewage samples from 49 wastewater facilities across the contiguous United States. Risk-based threshold (RBT) estimates varied across different mixture and sewage age scenarios. Fresh sewage RBT estimates were not always protective when aged sewage was present, and aged sewage RBT estimates often fell below the marker lower limit of quantification. Conservative RBT estimates of 9.3 × 10² and 9.1 × 10³ (copies/100 mL) for HF183/BacR287 and CPQ_056, respectively, were predicted when fresh sewage was greater (by volume) than aged at the time of measurement. Conversely, genetic markers may not be effective indicators when aged sewage contributes the majority of pathogens, relative to fresh contamination, but minimal marker levels. Results highlight the utility of QMRA that incorporates pollutant age and mixture scenarios, the potential advantages of a crAssphage fecal indicator, and the potential influence of site-specific factors on estimating RBT values.

Fecal pollution source characterization at non-point source impacted beaches under dry and wet weather conditions

Though Lake Michigan beaches in Chicago are not impacted by stormwater or wastewater outfalls, several of those beaches often exceed USEPA Beach Action Values (BAVs). We investigated the role of microbial source tracking (MST) as a complement to routine beach monitoring at Chicago beaches. In summer 2016, water samples from nine Chicago beaches were analyzed for E. coli by culture and enterococci by qPCR. A total of 195 archived samples were then tested for human (HF183/BacR287, HumM2), canine (DG3, DG37), and avian (GFD) microbial source tracking (MST) markers. Associations between MST and general fecal indicator bacteria (FIB) measures were evaluated and stratified based on wet and dry weather definitions. Among the 195 samples, HF183/BacR287 was quantifiable in 4%, HumM2 in 1%, DG3 in 6%, DG37 in 2%, and GFD in 23%. The one beach with a dog area was far more likely to have DG3 present in the quantifiable range than other beaches. Exceedance of general FIB BAVs increased the odds of human, dog and avian marker detection. MST marker weighted-average fecal scores for DG3 was 2.4 times, DG37 was 2.1 times, and GFD was 1.6 times higher during wet compared to dry weather conditions. HF183/BacR287 weighted-average fecal scores were not associated with precipitation. Associations between FIB BAV exceedance and MST marker detection were generally stronger in wet weather. Incorporating MST testing into routine beach water monitoring can provide information that beach managers can use when developing protection plans for beaches not impacted by point sources.

Large-scale implementation of standardized quantitative real-time PCR fecal source identification procedures in the Tillamook Bay Watershed

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.

Extended persistence of general and cattle-associated fecal indicators in marine and freshwater environment

Fecal contamination of recreational waters with cattle manure can pose a risk to public health due to the potential presence of various zoonotic pathogens. Fecal indicator bacteria (FIB) have a long history of use in the assessment of recreational water quality, but FIB quantification provides no information about pollution sources. Microbial source tracking (MST) markers have been developed in response to a need to identify pollution sources, yet factors that influence their decay in ambient waters are often poorly understood. We investigated the influence of water type (freshwater versus marine) and select environmental parameters (indigenous microbiota, ambient sunlight) on the decay of FIB and MST markers originating from cattle manure. Experiments were conducted in situ using a submersible aquatic mesocosm containing dialysis bags filled with a mixture of cattle manure and ambient water. Culturable FIB (E. coli, enterococci) were enumerated by membrane filtration and general fecal indicator bacteria (GenBac3, Entero1a, EC23S857) and MST markers (Rum2Bac, CowM2, CowM3) were estimated by qPCR. Water type was the most significant factor influencing decay (three-way ANOVA, p: 0.006 to <0.001), although the magnitude of the effect differed among microbial targets and over time. The presence of indigenous microbiota and exposure to sunlight were significantly correlated (three-way ANOVA, p: 0.044 to <0.001) with decay of enterococci and CowM2, while E. coli, EC23S857, Rum2Bac, and CowM3 (three-way ANOVA, p: 0.044 < 0.001) were significantly impacted by sunlight or indigenous microbiota. Results indicate extended persistence of both cultivated FIB and genetic markers in marine and freshwater water types. Findings suggest that multiple environmental stressors are important determinants of FIB and MST marker persistence, but their magnitude can vary across indicators. Selective exclusion of natural aquatic microbiota and/or sunlight typically resulted in extended survival, but the effect was minor and limited to select microbial targets.

Incidence of somatic and F+ coliphage in Great Lake Basin recreational waters

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 log₁₀ plaque forming units per liter and were consistently higher compared to F+ (non-detectable to 3.15 log₁₀ 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.

Evidence of Genetic Fecal Marker Interactions between Water Column and Periphyton in Artificial Streams

Periphyton is a complex mixture of algae, microbes, inorganic sediment, and organic matter that is attached to submerged surfaces in most flowing freshwater systems. This natural community is known to absorb pollutants from the water column, resulting in improved water quality. However, the role of periphyton in the fate and transport of genetic fecal markers suspended in the water column remains unclear. As application of genetic-based methodologies continues to increase in freshwater settings, it is important to identify any interactions that could potentially confound water quality interpretations. A 16 week indoor mesocosm study was conducted to simultaneously measure genetic fecal markers in the water column and in the associated periphyton when subject to wastewater source loading. Treated wastewater effluent was pumped directly from a treatment facility adjacent to the experimental stream facility. Inflow and outflow surface water grabs were paired with the collection of periphyton samples taken from the mesocosm substrates on a weekly basis. Samples were analyzed with three genetic fecal indicator quantitative real-time polymerase chain reaction assays targeting Escherichia coli (EC23S857), enterococci (Entero1), and Bacteroidales (GenBac3), as well as, two human host-associated fecal pollution markers (HF183 and HumM2). In addition, periphyton dry mass was measured. During wastewater effluent loading, genetic markers were detected in periphyton at frequencies up to 100% (EC23S857, Entero1, and GenBac3), 59.4% (HF183), and 21.9% (HumM2) confirming sequestration from the water column. Mean net-flux shifts in water column inflow and outflow genetic indicator concentrations further supported interactions between the periphyton and water column. In addition, positive correlations were observed between periphyton dry mass and genetic marker concentrations ranging from r = 0.693 (Entero1) to r = 0.911 (GenBac3). Overall, findings support the notion that genetic markers suspended in the water column can be trapped by periphyton, further suggesting that the benthic environment in flowing freshwater systems may be an important factor to consider for water quality management with molecular methods.

Comparison of somatic and F+ coliphage enumeration methods with large volume surface water samples

Coliphages are alternative fecal indicators that may be suitable surrogates for viral pathogens, but majority of standard detection methods utilize insufficient volumes for routine detection in environmental waters. We compared three somatic and F+ coliphage methods based on a paired measurement from 1 L samples collected from the Great Lakes (n = 74). Methods include: 1) dead-end hollow fiber ultrafilter with single agar layer (D-HFUF-SAL); 2) modified SAL (M-SAL); and 3) direct membrane filtration (DMF) technique. Overall, D-HFUF-SAL outperformed other methods as it yielded the lowest frequency of non-detects [(ND); 10.8%] and the highest average concentrations of recovered coliphage for positive samples (2.51 ± 1.02 [standard deviation, SD] log₁₀ plaque forming unit/liter (PFU/L) and 0.79 ± 0.71 (SD) log₁₀ PFU/L for somatic and F+, respectively). M-SAL yielded 29.7% ND and average concentrations of 2.26 ± 1.15 (SD) log₁₀ PFU/L (somatic) and 0.59 ± 0.82 (SD) log₁₀ PFU/L (F+ ). DMF performance was inferior to D-HFUF-SAL and M-SAL methods (ND of 65.6%; average somatic coliphage concentration 1.52 ± 1.32 [SD] log10 PFU/L, no F+ detected), indicating this procedure is unsuitable for 1 L surface water sample volumes. This study represents an important step toward the use of a coliphage method for recreational water quality criteria purposes.

Global Distribution of Human-Associated Fecal Genetic Markers in Reference Samples from Six Continents

Numerous bacterial genetic markers are available for the molecular detection of human sources of fecal pollution in environmental waters. However, widespread application is hindered by a lack of knowledge regarding geographical stability, limiting implementation to a small number of well-characterized regions. This study investigates the geographic distribution of five human-associated genetic markers (HF183/BFDrev, HF183/BacR287, BacHum-UCD, BacH, and Lachno2) in municipal wastewaters (raw and treated) from 29 urban and rural wastewater treatment plants (750-4 400 000 population equivalents) from 13 countries spanning six continents. In addition, genetic markers were tested against 280 human and nonhuman fecal samples from domesticated, agricultural and wild animal sources. Findings revealed that all genetic markers are present in consistently high concentrations in raw (median log₁₀ 7.2-8.0 marker equivalents (ME) 100 mL^-1) and biologically treated wastewater samples (median log₁₀ 4.6-6.0 ME 100 mL^-1) regardless of location and population. The false positive rates of the various markers in nonhuman fecal samples ranged from 5% to 47%. Results suggest that several genetic markers have considerable potential for measuring human-associated contamination in polluted environmental waters. This will be helpful in water quality monitoring, pollution modeling and health risk assessment (as demonstrated by QMRAcatch) to guide target-oriented water safety management across the globe.

A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method

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.

Quantitative CrAssphage PCR Assays for Human Fecal Pollution Measurement

Environmental waters are monitored for fecal pollution to protect public health and water resources. Traditionally, general fecal-indicator bacteria are used; however, they cannot distinguish human fecal waste from other animal pollution sources. Recently, a novel bacteriophage, crAssphage, was discovered by metagenomic data mining and reported to be abundant in and closely associated with human fecal waste. To confirm bioinformatic predictions, 384 primer sets were designed along the length of the crAssphage genome. Based on initial screening, two novel crAssphage qPCR assays (CPQ_056 and CPQ_064) were designed and evaluated in reference fecal samples and water matrices. The assays exhibited high specificities (98.6%) when tested against an animal fecal reference library, and crAssphage genetic markers were highly abundant in raw sewage and sewage-impacted water samples. In addition, CPQ_056 and CPQ_064 performance was compared to HF183/BacR287 and HumM2 assays in paired experiments. Findings confirm that viral crAssphage qPCR assays perform at a similar level to well-established bacterial human-associated fecal-source-identification approaches. These new viral-based assays could become important water quality management and research tools.

Differential decomposition of bacterial and viral fecal indicators in common human pollution types

Understanding the decomposition of microorganisms associated with different human fecal pollution types is necessary for proper implementation of many water quality management practices, as well as predicting associated public health risks. Here, the decomposition of select cultivated and molecular indicators of fecal pollution originating from fresh human feces, septage, and primary effluent sewage in a subtropical marine environment was assessed over a six day period with an emphasis on the influence of ambient sunlight and indigenous microbiota. Ambient water mixed with each fecal pollution type was placed in dialysis bags and incubated in situ in a submersible aquatic mesocosm. Genetic and cultivated fecal indicators including fecal indicator bacteria (enterococci, E. coli, and Bacteroidales), coliphage (somatic and F+), Bacteroides fragilis phage (GB-124), and human-associated genetic indicators (HF183/BacR287 and HumM2) were measured in each sample. Simple linear regression assessing treatment trends in each pollution type over time showed significant decay (p ≤ 0.05) in most treatments for feces and sewage (27/28 and 32/40, respectively), compared to septage (6/26). A two-way analysis of variance of log₁₀ reduction values for sewage and feces experiments indicated that treatments differentially impact survival of cultivated bacteria, cultivated phage, and genetic indicators. Findings suggest that sunlight is critical for phage decay, and indigenous microbiota play a lesser role. For bacterial cultivated and genetic indicators, the influence of indigenous microbiota varied by pollution type. This study offers new insights on the decomposition of common human fecal pollution types in a subtropical marine environment with important implications for water quality management applications.

Occurrence of Host-Associated Fecal Markers on Child Hands, Household Soil, and Drinking Water in Rural Bangladeshi Households

We evaluated whether provision and promotion of improved sanitation hardware (toilets and child feces management tools) reduced rotavirus and human fecal contamination of drinking water, child hands, and soil among rural Bangladeshi compounds enrolled in a cluster-randomized trial. We also measured host-associated genetic markers of ruminant and avian feces. We found evidence of widespread ruminant and avian fecal contamination in the compound environment; non-human fecal marker occurrence scaled with animal ownership. Strategies for controlling non- human fecal waste should be considered when designing interventions to reduce exposure to fecal contamination in low-income settings. Detection of a human- associated fecal marker and rotavirus was rare and unchanged by provision and promotion of improved sanitation to intervention compounds. The sanitation intervention reduced ruminant fecal contamination in drinking water and general (non-host specific) fecal contamination in soil but overall had limited effects on reducing fecal contamination in the household environment.

Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods

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.

Changes in bacterial and eukaryotic communities during sewage decomposition in Mississippi river water

Microbial decay processes are one of the mechanisms whereby sewage contamination is reduced in the environment. This decomposition process involves a highly complex array of bacterial and eukaryotic communities from both sewage and ambient waters. However, relatively little is known about how these communities change due to mixing and subsequent decomposition of the sewage contaminant. We investigated decay of sewage in upper Mississippi River using Illumina sequencing of 16S and 18S rRNA gene hypervariable regions and qPCR for human-associated and general fecal Bacteroidales indicators. Mixtures of primary treated sewage and river water were placed in dialysis bags and incubated in situ under ambient conditions for seven days. We assessed changes in microbial community composition under two treatments in a replicated factorial design: sunlight exposure versus shaded and presence versus absence of native river microbiota. Initial diversity was higher in sewage compared to river water for 16S sequences, but the reverse was observed for 18S sequences. Both treatments significantly shifted community composition for eukaryotes and bacteria (P < 0.05). Data indicated that the presence of native river microbiota, rather than exposure to sunlight, accounted for the majority of variation between treatments for both 16S (R = 0.50; P > 0.001) and 18S (R = 0.91; P = 0.001) communities. A comparison of 16S sequence data and fecal indicator qPCR measurements indicated that the latter was a good predictor of overall bacterial community change over time (rho: 0.804-0.814, P = 0.001). These findings suggest that biotic interactions, such as predation by bacterivorous protozoa, can be critical factors in the decomposition of sewage in freshwater habitats and support the use of Bacteroidales genetic markers as indicators of fecal pollution.

Factors affecting the presence of human-associated and fecal indicator real-time quantitative PCR genetic markers in urban-impacted recreational beaches

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.

Development of rapid canine fecal source identification PCR-based assays

The extent to which dogs contribute to aquatic fecal contamination is unknown despite the potential for zoonotic transfer of harmful human pathogens. We used genome fragment enrichment (GFE) to identify novel nonribosomal microbial genetic markers potentially useful for detecting dog fecal contamination with PCR-based methods in environmental samples. Of the 679 sequences obtained from GFE, we used 84 for the development of PCR assays targeting putative canine-associated genetic markers. Twelve genetic markers were shown to be prevalent among dog fecal samples and were rarely found in other animals. Three assays, DG3, DG37, and DG72, performed best in terms of specificity and sensitivity and were used for the development of SYBR Green and TaqMan quantitative PCR (qPCR) assays. qPCR analysis of 244 fecal samples collected from a wide geographic range indicated that marker concentrations were below limits of detection in noncanine hosts. As a proof-of-concept, these markers were detected in urban stormwater samples, suggesting a future application of newly developed methods for water quality monitoring.

Detection limits and cost comparisons of human- and gull-associated conventional and quantitative PCR assays in artificial and environmental waters

Some molecular methods for tracking fecal pollution in environmental waters have both PCR and quantitative PCR (qPCR) assays available for use. To assist managers in deciding whether to implement newer qPCR techniques in routine monitoring programs, we compared detection limits (LODs) and costs of PCR and qPCR assays with identical targets that are relevant to beach water quality assessment. For human-associated assays targeting Bacteroidales HF183 genetic marker, qPCR LODs were 70 times lower and there was no effect of target matrix (artificial freshwater, environmental creek water, and environmental marine water) on PCR or qPCR LODs. The PCR startup and annual costs were the lowest, while the per reaction cost was 62% lower than the Taqman based qPCR and 180% higher than the SYBR based qPCR. For gull-associated assays, there was no significant difference between PCR and qPCR LODs, target matrix did not effect PCR or qPCR LODs, and PCR startup, annual, and per reaction costs were lower. Upgrading to qPCR involves greater startup and annual costs, but this increase may be justified in the case of the human-associated assays with lower detection limits and reduced cost per sample.

Characterization of fecal concentrations in human and other animal sources by physical, culture-based, and quantitative real-time PCR methods

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.

Enterococcus and Escherichia coli fecal source apportionment with microbial source tracking genetic markers--is it feasible?

Fecal pollution is measured in surface waters using culture-based measurements of enterococci and Escherichia coli bacteria. Source apportionment of these two fecal indicator bacteria is an urgent need for prioritizing remediation efforts and quantifying health risks associated with source-specific pathogens. There are a number of quantitative real-time PCR (QPCR) assays that estimate concentrations of source-associated genetic markers; however, their concentrations are not necessarily amenable to source apportionment because the markers may differ in prevalence across sources. Here we mathematically derive and test, under ideal conditions, a method that utilizes the ratios of fecal source-associated genetic markers and culture and molecular measurements of general fecal indicators to apportion enterococci and E. coli. The source contribution is approximately equal to the ratio of the source-associated and the general fecal indicator concentrations in a water sample divided by their ratio in the source material, so long as cross-reactivity is negligible. We illustrate the utility of the ratio method using samples consisting of mixtures of various fecal pollution sources. The results from the ratio method correlated well with the actual source apportionment in artificial samples. However, aging of contamination can confound source allocation predictions. In particular, culturable enterococci and E. coli, the organisms presently regulated in the United States and much of the world, decay at different rates compared to source-associated markers and as a result cannot be apportioned using this method. However, limited data suggest a similar decay rate between source-associated and QPCR-measured Enterococcus and E. coli genetic markers, indicating that apportionment may be possible for these organisms; however further work is needed to confirm.

Recommendations following a multi-laboratory comparison of microbial source tracking methods

Microbial source tracking (MST) methods were evaluated in the Source Identification Protocol Project (SIPP), in which 27 laboratories compared methods to identify host sources of fecal pollution from blinded water samples containing either one or two different fecal types collected from California. This paper details lessons learned from the SIPP study and makes recommendations to further advance the field of MST. Overall, results from the SIPP study demonstrated that methods are available that can correctly identify whether particular host sources including humans, cows and birds have contributed to contamination in a body of water. However, differences between laboratory protocols and data processing affected results and complicated interpretation of MST method performance in some cases. This was an issue particularly for samples that tested positive (non-zero Ct values) but below the limits of quantification or detection of a PCR assay. Although false positives were observed, such samples in the SIPP study often contained the fecal pollution source that was being targeted, i.e., the samples were true positives. Given these results, and the fact that MST often requires detection of targets present in low concentrations, we propose that such samples be reported and identified in a unique category to facilitate data analysis and method comparisons. Important data can be lost when such samples are simply reported as positive or negative. Actionable thresholds were not derived in the SIPP study due to limitations that included geographic scope, age of samples, and difficulties interpreting low concentrations of target in environmental samples. Nevertheless, the results of the study support the use of MST for water management, especially to prioritize impaired waters in need of remediation. Future integration of MST data into quantitative microbial risk assessments and other models could allow managers to more efficiently protect public health based on site conditions.

Evaluation of the repeatability and reproducibility of a suite of qPCR-based microbial source tracking methods

Many PCR-based methods for microbial source tracking (MST) have been developed and validated within individual research laboratories. Inter-laboratory validation of these methods, however, has been minimal, and the effects of protocol standardization regimes have not been thoroughly evaluated. Knowledge of factors influencing PCR in different laboratories is vital to future technology transfer for use of MST methods as a tool for water quality management. In this study, a blinded set of 64 filters (containing 32 duplicate samples generated from 12 composite fecal sources) were analyzed by three to five core laboratories with a suite of PCR-based methods utilizing standardized reagents and protocols. Repeatability (intra-laboratory variability) and reproducibility (inter-laboratory variability) of observed results were assessed. When standardized methodologies were used, intra- and inter-laboratory %CVs were generally low (median %CV 0.1-3.3% and 1.9-7.1%, respectively) and comparable to those observed in similar inter-laboratory validation studies performed on other methods of quantifying fecal indicator bacteria (FIB) in environmental samples. ANOVA of %CV values found three human-associated methods (BsteriF1, BacHum, and HF183Taqman) to be similarly reproducible (p > 0.05) and significantly more reproducible (p < 0.05) than HumM2. This was attributed to the increased variability associated with low target concentrations detected by HumM2 (approximately 1-2 log10copies/filter lower) compared to other human-associated methods. Cow-associated methods (BacCow and CowM2) were similarly reproducible (p > 0.05). When using standardized protocols, variance component analysis indicated sample type (fecal source and concentration) to be the major contributor to total variability with that from replicate filters and inter-laboratory analysis to be within the same order of magnitude but larger than inherent intra-laboratory variability. However, when reagents and protocols were not standardized, inter-laboratory %CV generally increased with a corresponding decline in reproducibility. Overall, these findings verify the repeatability and reproducibility of these MST methods and highlight the need for standardization of protocols and consumables prior to implementation of larger scale MST studies involving multiple laboratories.

Comparison of PCR and quantitative real-time PCR methods for the characterization of ruminant and cattle fecal pollution sources

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.

Performance evaluation of canine-associated Bacteroidales assays in a multi-laboratory comparison study

The contribution of fecal pollution from dogs in urbanized areas can be significant and is an often underestimated problem. Microbial source tracking methods (MST) utilizing quantitative PCR of dog-associated gene sequences encoding 16S rRNA of Bacteroidales are a useful tool to estimate these contributions. However, data about the performance of available assays are scarce. The results of a multi-laboratory study testing two assays for the determination of dog-associated Bacteroidales (DogBact and BacCan-UCD) on 64 single and mixed fecal source samples created from pooled fecal samples collected in California are presented here. Standardization of qPCR data treatment lowered inter-laboratory variability of sensitivity and specificity results. Both assays exhibited 100% sensitivity. Normalization methods are presented that eliminated random and confirmed non-target responses. The combination of standardized qPCR data treatment, use of normalization via a non-target specific Bacteroidales assay (GenBac3), and application of threshold criteria improved the calculated specificity significantly for both assays. Such measures would reasonably improve MST data interpretation not only for canine-associated assays, but for all qPCR assays used in identifying and monitoring fecal pollution in the environment.

Performance of forty-one microbial source tracking methods: a twenty-seven lab evaluation study

The last decade has seen development of numerous new microbial source tracking (MST) methodologies, but many of these have been tested in just a few laboratories with a limited number of fecal samples. This method evaluation study examined the specificity and sensitivity of 41 MST methodologies by analyzing data generated in 27 laboratories. MST methodologies that targeted human, cow, ruminant, dog, gull, pig, horse, and sheep were tested against sewage, septage, human, cow, dog, deer, pig, chicken, pigeon, gull, horse, and goose fecal samples. Each laboratory received 64 blind samples containing a single source (singletons) or two sources (doubletons), as well as diluted singleton samples to assess method sensitivity. Laboratories utilized their own protocols when performing the methods and data were deposited in a central database before samples were unblinded. Between one and seven laboratories tested each method. The most sensitive and specific assays, based on an analysis of presence/absence of each marker in target and non-target fecal samples, were HF183 endpoint and HF183SYBR (human), CF193 and Rum2Bac (ruminant), CowM2 and CowM3 (cow), BacCan (dog), Gull2SYBR and LeeSeaGull (gull), PF163 and pigmtDNA (pig), HoF597 (horse), PhyloChip (pig, horse, chicken, deer), Universal 16S TRFLP (deer), and Bacteroidales 16S TRFLP (pig, horse, chicken, deer); all had sensitivity and specificity higher than 80% in all or the majority of laboratories. When the abundance of MST markers in target and non-target fecal samples was examined, some assays that performed well in the binary analysis were found to not be sensitive enough as median concentrations fell below a minimum abundance criterion (set at 50 copies per colony forming units of enterococci) in target fecal samples. Similarly, some assays that cross-reacted with non-target fecal sources in the binary analysis were found to perform well in a quantitative analysis because the cross-reaction occurred at very low levels. Based on a quantitative analysis, the best performing methods were HF183Taqman and BacH (human), Rum2Bac and BacR (ruminant), LeeSeaGull (gull), and Pig2Bac (pig); no cow or dog-specific assay met the quantitative specificity and sensitivity criteria. Some of the best performing assays in the study were run by just one laboratory so further testing of assay portability is needed. While this study evaluated the marker performance in defined samples, further field testing as well as development of frameworks for fecal source allocation and risk assessment are needed.

Performance of forty-one microbial source tracking methods: a twenty-seven lab evaluation study

The last decade has seen development of numerous new microbial source tracking (MST) methodologies, but many of these have been tested in just a few laboratories with a limited number of fecal samples. This method evaluation study examined the specificity and sensitivity of 41 MST methodologies by analyzing data generated in 27 laboratories. MST methodologies that targeted human, cow, ruminant, dog, gull, pig, horse, and sheep were tested against sewage, septage, human, cow, dog, deer, pig, chicken, pigeon, gull, horse, and goose fecal samples. Each laboratory received 64 blind samples containing a single source (singletons) or two sources (doubletons), as well as diluted singleton samples to assess method sensitivity. Laboratories utilized their own protocols when performing the methods and data were deposited in a central database before samples were unblinded. Between one and seven laboratories tested each method. The most sensitive and specific assays, based on an analysis of presence/absence of each marker in target and non-target fecal samples, were HF183 endpoint and HF183SYBR (human), CF193 and Rum2Bac (ruminant), CowM2 and CowM3 (cow), BacCan (dog), Gull2SYBR and LeeSeaGull (gull), PF163 and pigmtDNA (pig), HoF597 (horse), PhyloChip (pig, horse, chicken, deer), Universal 16S TRFLP (deer), and Bacteroidales 16S TRFLP (pig, horse, chicken, deer); all had sensitivity and specificity higher than 80% in all or the majority of laboratories. When the abundance of MST markers in target and non-target fecal samples was examined, some assays that performed well in the binary analysis were found to not be sensitive enough as median concentrations fell below a minimum abundance criterion (set at 50 copies per colony forming units of enterococci) in target fecal samples. Similarly, some assays that cross-reacted with non-target fecal sources in the binary analysis were found to perform well in a quantitative analysis because the cross-reaction occurred at very low levels. Based on a quantitative analysis, the best performing methods were HF183Taqman and BacH (human), Rum2Bac and BacR (ruminant), LeeSeaGull (gull), and Pig2Bac (pig); no cow or dog-specific assay met the quantitative specificity and sensitivity criteria. Some of the best performing assays in the study were run by just one laboratory so further testing of assay portability is needed. While this study evaluated the marker performance in defined samples, further field testing as well as development of frameworks for fecal source allocation and risk assessment are needed.

Sewage reflects the distribution of human faecal Lachnospiraceae

Faecal pollution contains a rich and diverse community of bacteria derived from animals and humans, many of which might serve as alternatives to the traditional enterococci and Escherichia coli faecal indicators. We used massively parallel sequencing (MPS) of the 16S rRNA gene to characterize microbial communities from wastewater treatment plant (WWTP) influent sewage from 12 cities geographically distributed across the USA. We examined members of the Clostridiales, which included the families Clostridiaceae, Lachnospiraceae and Ruminococcaceae for their potential as sewage indicators. Lachnospiraceae was one of the most abundant groups of faecal bacteria in sewage, and several Lachnospiraceae high-abundance sewage pyrotags occurred in at least 46 of 48 human faecal samples. Clone libraries targeting Clostridium coccoides (C. coccoides) in sewage samples demonstrated that Lachnospiraceae-annotated V6 pyrotags encompassed the previously reported C. coccoides group. We used oligotyping to profile the genus Blautia within Lachnospiraceae and found oligotypes comprised of 24 entropy components that showed patterns of host specificity. These findings suggest that indicators based on Blautia might have the capacity to discriminate between different faecal pollution sources. Development of source-specific alternative indicators would enhance water quality assessments, which leads to improved ecosystem health and reduced human health risk due to waterborne disease.

Dramatic improvements in beach water quality following gull removal

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.

Interlaboratory comparison of real-time PCR protocols for quantification of general fecal indicator bacteria

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.

Differential decay of human faecal Bacteroides in marine and freshwater

Genetic markers from Bacteroides and other faecal bacteria are being tested for inclusion in regulations to quantify aquatic faecal contamination and estimate public health risk. For the method to be used quantitatively across environments, persistence and decay of markers must be understood. We measured concentrations of contaminant molecular markers targeting Enterococcus and Bacteroides spp. in marine and freshwater microcosms spiked with human sewage and exposed to either sunlight or dark treatments. We used Bayesian statistics with a delayed Chick-Watson model to estimate kinetic parameters for target decay. DNA- and RNA-based targets decayed at approximately the same rate. Molecular markers persisted (could be detected) longer in marine water. Sunlight increased the decay rates of cultured indicators more than those of molecular markers; sunlight also limited persistence of molecular markers. Within each treatment, Bacteroides markers had similar decay profiles, but some Bacteroides markers significantly differed in decay rates. The role of extracellular DNA in persistence appeared unimportant in the microcosms. Because conditions were controlled, microcosms allowed the effects of specific environmental variables on marker persistence and decay to be measured. While marker decay profiles in more complex environments would be expected to vary from those observed here, the differences we measured suggest that water matrix is an important factor affecting quantitative source tracking and microbial risk assessment applications.

Combining land use information and small stream sampling with PCR-based methods for better characterization of diffuse sources of human fecal pollution

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.

Decay of bacterial pathogens, fecal indicators, and real-time quantitative PCR genetic markers in manure-amended soils

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria (FIB), and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manure-amended agricultural soils. Known concentrations of transformed green fluorescent protein-expressing Escherichia coli O157:H7/pZs and red fluorescent protein-expressing Salmonella enterica serovar Typhimurium/pDs were added to laboratory-scale manure-amended soil microcosms with moisture contents of 60% or 80% field capacity and incubated at temperatures of -20°C, 10°C, or 25°C for 120 days. A two-stage first-order decay model was used to determine stage 1 and stage 2 first-order decay rate coefficients and transition times for each organism and qPCR genetic marker in each treatment. Genetic markers for FIB (Enterococcus spp., E. coli, and Bacteroidales) exhibited decay rate coefficients similar to that of E. coli O157:H7/pZs but not of S. enterica serovar Typhimurium/pDs and persisted at detectable levels longer than both pathogens. Concentrations of these two bacterial pathogens, their counterpart qPCR genetic markers (stx1 and ttrRSBCA, respectively), and FIB genetic markers were also correlated (r = 0.528 to 0.745). This suggests that these qPCR genetic markers may be reliable conservative surrogates for monitoring fecal pollution from manure-amended land. Host-associated qPCR genetic markers for microbial source tracking decayed rapidly to nondetectable concentrations, long before FIB, Salmonella enterica serovar Typhimurium/pDs, and E. coli O157:H7/pZs. Although good indicators of point source or recent nonpoint source fecal contamination events, these host-associated qPCR genetic markers may not be reliable indicators of nonpoint source fecal contamination events that occur weeks following manure application on land.

Improved strategies and optimization of calibration models for real-time PCR absolute quantification

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.

Performance of PCR-based assays targeting Bacteroidales genetic markers of human fecal pollution in sewage and fecal samples

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.

A Bayesian method for calculating real-time quantitative PCR calibration curves using absolute plasmid DNA standards

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.