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 revolutionized water quality analysis yet?

The impacts of nucleic acid-based methods - such as PCR and sequencing - to detect and analyze indicators, genetic markers or molecular signatures of microbial faecal pollution 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 (>1100 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 revolutionized faecal pollution detection (i.e., traditional or alternative general faecal indicator/marker analysis) and microbial source tracking (i.e., host-associated faecal indicator/marker analysis), 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 standardized 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 discusses 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.

Standards to support an enduring capability in wastewater surveillance for public health: Where are we?

The COVID-19 pandemic highlighted a wide range of public health system challenges for infectious disease surveillance. The discovery that the SARS-CoV-2 virus was shed in feces and can be characterized using PCR-based testing of sewage samples offers new possibilities and challenges for wastewater surveillance (WWS). However, WWS standardization of practices is needed to provide actionable data for a public health response. A workshop was convened consisting of academic, federal government, and industry stakeholders. The objective was to review WWS sampling protocols, testing methods, analyses, and data interpretation approaches for WWS employed nationally and identify opportunities for standardizing practices, including the development of documentary standards or reference materials in the case of SARS-CoV-2 surveillance. Other WWS potential future threats to public health were also discussed. Several aspects of WWS were considered and each offers the opportunity for standards development. These areas included sampling strategies, analytical methods, and data reporting practices. Each of these areas converged on a common theme, the challenge of results comparability across facilities and jurisdictions. For sampling, the consensus solution was the development of documentary standards to guide appropriate sampling practices. In contrast, the predominant opportunity for analytical methods was reference material development, such as PCR-based standards and surrogate recovery controls. For data reporting practices, the need for establishing the minimal required metadata, a metadata vocabulary, and standardizing data units of measure including measurement threshold definitions was discussed. Beyond SARS-CoV-2 testing, there was general agreement that the WWS platform will continue to be a valuable tool for a wide range of public health threats and that future cross-sector engagements are needed to guide an enduring WWS capability.

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.

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.

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.

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.

Viral and Bacterial Fecal Indicators in Untreated Wastewater across the Contiguous United States Exhibit Geospatial Trends.

Cultivated fecal indicator bacteria such as Escherichia coli and enterococci are typically used to assess the sanitary quality of recreational waters. However, these indicators suffer from several limitations, such as the length of time needed to obtain results and the fact that they are commensal inhabitants of the gastrointestinal tract of many animals and have fate and transport characteristics dissimilar to pathogenic viruses. Numerous emerging technologies that offer same-day water quality results or pollution source information or that more closely mimic persistence patterns of disease-causing pathogens that may improve water quality management are now available, but data detailing geospatial trends in wastewater across the United States are sparse. We report geospatial trends of cultivated bacteriophage (somatic, F+, and total coliphages and GB-124 phage), as well as genetic markers targeting polyomavirus, enterococci, E. coli, Bacteroidetes, and human-associated Bacteroides spp. (HF183/BacR287 and HumM2) in 49 primary influent sewage samples collected from facilities across the contiguous United States. Samples were selected from rural and urban facilities spanning broad latitude, longitude, elevation, and air temperature gradients by using a geographic information system stratified random site selection procedure. Most indicators in sewage demonstrated a remarkable similarity in concentration regardless of location. However, some exhibited predictable shifts in concentration based on either facility elevation or local air temperature. Geospatial patterns identified in this study, or the absence of such patterns, may have several impacts on the direction of future water quality management research, as well as the selection of alternative metrics to estimate sewage pollution on a national scale.IMPORTANCE This study provides multiple insights to consider for the application of bacterial and viral indicators in sewage to surface water quality monitoring across the contiguous United States, ranging from method selection considerations to future research directions. Systematic testing of a large collection of sewage samples confirmed that crAssphage genetic markers occur at a higher average concentration than key human-associated Bacteroides spp. on a national scale. Geospatial testing also suggested that some methods may be more suitable than others for widespread implementation. Nationwide characterization of indicator geospatial trends in untreated sewage represents an important step toward the validation of these newer methods for future water quality monitoring applications. In addition, the large paired-measurement data set reported here affords the opportunity to conduct a range of secondary analyses, such as the generation of new or updated quantitative microbial risk assessment models used to estimate public health risk.

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.

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.

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.