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

Quantitative fecal pollution assessment with bacterial, viral, and molecular methods in small stream tributaries

Stream water quality can be impacted by a myriad of fecal pollution sources and waste management practices. Identifying origins of fecal contamination can be challenging, especially in high order streams where water samples are influenced by pollution from large drainage areas. Strategic monitoring of tributaries can be an effective strategy to identify conditions that influence local water quality. Water quality is assessed using fecal indicator bacteria (FIB); however, FIB cannot differentiate sources of fecal contamination nor indicate the presence of disease-causing viruses. Under different land use scenarios, three small stream catchments were investigated under 'wet' and 'dry' conditions (Scenario 1: heavy residential; Scenario 2: rural residential; and Scenario 3: undeveloped/agricultural). To identify fecal pollution trends, host-associated genetic targets HF183/BacR287 (human), Rum2Bac (ruminant), GFD (avian), and DG3 (canine) were analyzed along with FIB (Escherichia coli and enterococci), viral indicators (somatic and F+ coliphage), six general water quality parameters, and local rainfall. Levels of E. coli exceeded single sample maximum limits (235 CFU/100 mL) in 70.7 % of samples, enterococci (70 CFU/100 mL) in 100 % of samples, and somatic coliphage exceeded advisory thresholds (600 PFU/L) in 34.1 % of samples. The detection frequency for the human-associated genetic marker was highest in Scenario 3 (50 % of samples) followed by Scenario 2 (46 %), while the ruminant-associated marker was most prevalent in Scenario 1 (64 %). Due to the high proportion of qPCR-based measurements below the limit of quantification, a Bayesian data analysis approach was applied to investigate links between host-associated genetic marker occurrence with that of rainfall and fecal indicator levels. Multiple trends associated with small stream monitoring were revealed, emphasizing the role of rainfall, the utility of fecal source information to improve water quality management. And furthermore, water quality monitoring with bacterial or viral methodologies can alter the interpretation of fecal pollution sources in impaired waters.

The comparison of decay rates of infectious SARS-CoV-2 and viral RNA in environmental waters and wastewater

Understanding the decay characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater and ambient waters is important for multiple applications including assessment of risk of exposure associated with handling wastewater samples, public health risk associated with recreation in wastewater polluted ambient waters and better understanding and interpretation of wastewater-based epidemiology (WBE) results. We evaluated the decay rates of infectious SARS-CoV-2 and viral RNA in wastewater and ambient waters under temperature regimes representative of seasonal fluctuations. Infectious virus was seeded in autoclaved primary wastewater effluent, final dechlorinated wastewater effluent, lake water, and marine water at a final concentration of 6.26 ± 0.07 log10 plaque forming units per milliliter. Each suspension was incubated at either 4°, 25°, and 37 °C. Samples were initially collected on an hourly basis, then approximately every other day for 15 days. All samples were analyzed for infectious virus via a plaque assay using the Vero E6 cell line, and viral gene copy levels were quantified with the US CDC's N1 and N2 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assays. The infectious virus decayed significantly faster (p ≤ 0.0214) compared to viral RNA, which persisted for the duration of the study irrespective of the incubation conditions. The initial loss (within 15 min of seeding) as well as decay of infectious SARS-CoV-2 was significantly faster (p ≤ 0.0387) in primary treated wastewater compared to other water types, but viral RNA did not degrade appreciably in this matrix until day 15. Overall, temperature was the most important driver of decay, and after 24 h, no infectious SARS-CoV-2 was detected at 37 °C in any water type. Moreover, the CDC N2 gene assay target decayed significantly (p ≤ 0.0174) faster at elevated temperatures compared to CDC N1, which has important implications for RT-qPCR assay selection for WBE approach.

Application of a microbial and pathogen source tracking toolbox to identify infrastructure problems in stormwater drainage networks: a case study

Water scarcity and increasing urbanization are forcing municipalities to consider alternative water sources, such as stormwater, to fill in water supply gaps or address hydromodification of receiving urban streams. Mounting evidence suggests that stormwater is often contaminated with human feces, even in stormwater drainage systems separate from sanitary sewers. Pinpointing sources of human contamination in drainage networks is challenging given the diverse sources of fecal pollution that can impact these systems and the non-specificity of traditional fecal indicator bacteria (FIB) for identifying these host sources. As such, we used a toolbox approach that encompassed microbial source tracking (MST), FIB monitoring, and bacterial pathogen monitoring to investigate microbial contamination of stormwater in an urban municipality. We demonstrate that human sewage frequently contaminated stormwater (in >50% of routine samples), based on the presence of the human fecal marker HF183, and often exceeded microbial water quality criteria. Arcobacter butzleri, a pathogen of emerging concern, was also detected in >50% of routine samples, with 75% of these pathogen-positive samples also being positive for the human fecal marker HF183, suggesting human municipal sewage as the likely source for this pathogen. MST and FIB were used to track human fecal pollution in the drainage network to the most likely point source of contamination, for which a sewage cross-connection was identified and confirmed using tracer dyes. These results point to the ubiquitous presence of human sewage in stormwater and also provide municipalities with the tools to identify sources of anthropogenic contamination in storm drainage networks.IMPORTANCEWater scarcity, increased urbanization, and population growth are driving municipalities worldwide to consider stormwater as an alternative water source in urban environments. However, many studies suggest that stormwater is relatively poor in terms of microbial water quality, is frequently contaminated with human sewage, and therefore could represent a potential health risk depending on the type of exposure (e.g., irrigation of community gardens). Traditional monitoring of water quality based on fecal bacteria does not provide any information about the sources of fecal pollution contaminating stormwater (i.e., animals/human feces). Herein, we present a case study that uses fecal bacterial monitoring, microbial source tracking, and bacterial pathogen analysis to identify a cross-connection that contributed to human fecal intrusion into an urban stormwater network. This microbial toolbox approach can be useful for municipalities in identifying infrastructure problems in stormwater drainage networks to reduce risks associated with water reuse.

Quantitative fecal source characterization of urban municipal storm sewer system outfall 'wet' and 'dry' weather discharges

Urban areas are built environments containing substantial amounts of impervious surfaces (e.g., streets, sidewalks, roof tops). These areas often include elaborately engineered drainage networks designed to collect, transport, and discharge untreated stormwater into local surface waters. When left uncontrolled, these discharges may contain unsafe levels of fecal waste from sources such as sanitary sewage and wildlife even under dry weather conditions. This study evaluates paired measurements of host-associated genetic markers (log10 copies per reaction) indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), canine (DG3), and avian (GFD) fecal sources, 12-hour cumulative precipitation (mm), four catchment land use metrics determined by global information system (GIS) mapping, and Escherichia coli (MPN/100 ml) from seven municipal separate storm sewer system outfall locations situated at the southern portion of the Anacostia River Watershed (District of Columbia, U.S.A.). A total of 231 discharge samples were collected twice per month (n = 24 sampling days) and after rain events (n = 9) over a 13-month period. Approximately 50 % of samples (n = 116) were impaired, exceeding the local E. coli single sample maximum of 2.613 log10 MPN/100 ml. Genetic quality controls indicated the absence of amplification inhibition in 97.8 % of samples, however 14.7 % (n = 34) samples showed bias in DNA recovery. Of eligible samples, quantifiable levels were observed for avian (84.1 %), human (57.4 % for HF183/BacR287 and 40 % for HumM2), canine (46.7 %), and ruminant (15.9 %) host-associated genetic markers. Potential links between paired measurements are explored with a recently developed Bayesian qPCR censored data analysis approach. Findings indicate that human, pet, and urban wildlife all contribute to storm outfall discharge water quality in the District of Columbia, but pollutant source contributions vary based on 'wet' and 'dry' conditions and catchment land use, demonstrating that genetic-based fecal source identification methods combined with GIS land use mapping can complement routine E. coli monitoring to improve stormwater management in urban areas.

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.

Microbial source tracking using molecular and cultivable methods in a tropical mixed-use drinking water source to support water safety plans

Microbial contamination deteriorates source water quality, posing a severe problem for drinking water suppliers worldwide and addressed by the Water Safety Plan framework to ensure high-quality and reliable drinking water. Microbial source tracking (MST) is used to examine different microbial pollution sources via host-specific intestinal markers for humans and different types of animals. However, the application of MST in tropical surface water catchments that provide raw water for drinking water supplies is limited. We analyzed a set of MST markers, namely, three cultivable bacteriophages and four molecular PCR and qPCR assays, together with 17 microbial and physicochemical parameters, to identify fecal pollution from general, human-, swine-, and cattle-specific sources. Seventy-two river water samples at six sampling sites were collected over 12 sampling events during wet and dry seasons. We found persistent fecal contamination via the general fecal marker GenBac3 (100 % detection; 2.10-5.42 log₁₀ copies/100 mL), with humans (crAssphage; 74 % detection; 1.62-3.81 log₁₀ copies/100 mL) and swine (Pig-2-Bac; 25 % detection; 1.92-2.91 log₁₀ copies/100 mL). Higher contamination levels were observed during the wet season (p < 0.05). The conventional PCR screening used for the general and human markers showed 94.4 % and 69.8 % agreement with the respective qPCR results. Specifically, in the studied watershed, coliphage could be a screening parameter for the crAssphage marker (90.6 % and 73.7 % positive and negative predictive values; Spearman's rank correlation coefficient = 0.66; p < 0.001). The likelihood of detecting the crAssphage marker significantly increased when total and fecal coliforms exceeded 20,000 and 4000 MPN/100 mL, respectively, as Thailand Surface Water Quality Standards, with odds ratios and 95 % confidence intervals of 15.75 (4.43-55.98) and 5.65 (1.39-23.05). Our study confirms the potential benefits of incorporating MST monitoring into water safety plans, supporting the use of this approach to ensure high-quality drinking water supplies worldwide.

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.

Fecal indicators and antibiotic resistance genes exhibit diurnal trends in the Chattahoochee River: Implications for water quality monitoring

Water bodies that serve as sources of drinking or recreational water are routinely monitored for fecal indicator bacteria (FIB) by state and local agencies. Exceedances of monitoring thresholds set by those agencies signal likely elevated human health risk from exposure, but FIB give little information about the potential source of contamination. To improve our understanding of how within-day variation could impact monitoring data interpretation, we conducted a study at two sites along the Chattahoochee River that varied in their recreational usage and adjacent land-use (natural versus urban), collecting samples every 30 min over one 24-h period. We assayed for three types of microbial indicators: FIB (total coliforms and Escherichia coli); human fecal-associated microbial source tracking (MST) markers (crAssphage and HF183/BacR287); and a suite of clinically relevant antibiotic resistance genes (ARGs; blaCTX-M, blaCMY, MCR, KPC, VIM, NDM) and a gene associated with antibiotic resistance (intl1). Mean levels of FIB and clinically relevant ARGs (blaCMY and KPC) were similar across sites, while MST markers and intI1 occurred at higher mean levels at the natural site. The human-associated MST markers positively correlated with antibiotic resistant-associated genes at both sites, but no consistent associations were detected between culturable FIB and any molecular markers. For all microbial indicators, generalized additive mixed models were used to examine diurnal variability and whether this variability was associated with environmental factors (water temperature, turbidity, pH, and sunlight). We found that FIB peaked during morning and early afternoon hours and were not associated with environmental factors. With the exception of HF183/BacR287 at the urban site, molecular MST markers and intI1 exhibited diurnal variability, and water temperature, pH, and turbidity were significantly associated with this variability. For blaCMY and KPC, diurnal variability was present but was not correlated with environmental factors. These results suggest that differences in land use (natural or urban) both adjacent and upstream may impact overall levels of microbial contamination. Monitoring agencies should consider matching sample collection times with peak levels of target microbial indicators, which would be in the morning or early afternoon for the fecal associated indicators. Measuring multiple microbial indicators can lead to clearer interpretations of human health risk associated with exposure to contaminated water.

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.

Influence of temperature and water quality on the persistence of human mitochondrial DNA, human Hf183 Bacteroidales, fecal coliforms and enterococci in surface water in human fecal source tracking context

Mitochondrial DNA (mtDNA) is used as a genetic marker to track fecal contamination in surface water. Its potential to effectively discriminate between the nonpoint sources of fecal pollution (e.g. human, livestock) in water environments is relevant for water quality management. However, there is a lack of knowledge about the environmental persistence of mtDNA in relation to those of other microbial parameters, such as fecal indicator bacteria (FIB). In this study, mesocosms composed of water collected from four rivers and tap water were spiked with raw wastewater to mimic human fecal contamination. Mesocosms composed of raw wastewater were also studied. The mesocosms were incubated at 4 °C or at 22 °C for 189 days, from which the levels of human mtDNA (HumtDNA) and human Bacteroidales (Hf183) were measured by qPCR. The levels of FIB (fecal coliforms and enterococci) and heterotrophs were determined by culture methods along with the determination of physicochemical attributes. The decay rates of the genetic markers and FIB were determined with first-order decay rate models. The decay rates of HumtDNA (0.004-0.059 d^-1), Hf183 (0.007-0.082 d^-1), and the two FIBs (0.005-0.066 d^-1) were similar at 4 °C, while the genetic markers both had higher decay rates (0.013-0.919 d^-1) at 22 °C. Different HumtDNA decay rates were observed between the river mesocosms (0.043-0.919 d^-1) and the wastewater and tap water mesocosms (0.004-0.095 d^-1). Covariations of pH and conductivity among the HumtDNA, Hf183 and FIB decay rates were observed. HumtDNA and Hf183 had similar environmental persistence, whereas fecal coliforms and enterococci persisted longer at 22 °C. Finally, HumtDNA had the same trends of persistence in the four river mesocosms, suggesting a relative stability of this marker in different rivers. Our results suggest that HumtDNA could be more suitable for tracking the source of a recent fecal contamination in complement to FIB.

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.

Identifying Inorganic Turbidity in Water Samples as Potential Loss Factor During Nucleic Acid Extraction: Implications for Molecular Fecal Pollution Diagnostics and Source Tracking

Molecular diagnostic methods are increasingly applied for food and environmental analysis. Since several steps are involved in sample processing which can affect the outcome (e.g., adhesion of DNA to the sample matrix, inefficient precipitation of DNA, pipetting errors and (partial) loss of the DNA pellet during DNA isolation), quality control is essential at all processing levels. In soil microbiology, particular attention has been paid to the inorganic component of the sample matrix affecting DNA extractability. In water quality testing, however, this aspect has mostly been neglected so far, although it is conceivable that these mechanisms have a similar impact. The present study was therefore dedicated to investigate possible matrix effects on results of water quality analysis. Field testing in an aquatic environment with pronounced chemo-physical gradients [total suspended solids (TSS), inorganic turbidity, total organic carbon (TOC), and conductivity] indicated a negative association between DNA extractability (using a standard phenol/chloroform extraction procedure) and turbidity (spearman ρ = −0.72, p < 0.001, n = 21). Further detailed laboratory experiments on sediment suspensions confirmed the hypothesis of inorganic turbidity being the main driver for reduced DNA extractability. The observed effects, as known from soil samples, were also indicated to result from competitive effects for free charges on clay minerals, leading to adsorption of DNA to these inorganic particles. A protocol modification by supplementing the extraction buffer with salmon sperm DNA, to coat charged surfaces prior to cell lysis, was then applied on environmental water samples and compared to the standard protocol. At sites characterized by high inorganic turbidity, DNA extractability was significantly improved or made possible in the first place by applying the adapted protocol. This became apparent from intestinal enterococci and microbial source tracking (MST)-marker levels measured by quantitative polymerase chain reaction (qPCR) (100 to 10,000-fold median increase in target concentrations). The present study emphasizes the need to consider inorganic turbidity as a potential loss factor in DNA extraction from water-matrices. Negligence of these effects can lead to a massive bias, by up to several orders of magnitude, in the results of molecular MST and fecal pollution diagnostics.

The Environmental Microbiology Minimum Information (EMMI) Guidelines: qPCR and dPCR Quality and Reporting for Environmental Microbiology

Real-time quantitative polymerase chain reaction (qPCR) and digital PCR (dPCR) methods have revolutionized environmental microbiology, yielding quantitative organism-specific data of nucleic acid targets in the environment. Such data are essential for characterizing interactions and processes of microbial communities, assessing microbial contaminants in the environment (water, air, fomites), and developing interventions (water treatment, surface disinfection, air purification) to curb infectious disease transmission. However, our review of recent qPCR and dPCR literature in our field of health-related environmental microbiology showed that many researchers are not reporting necessary and sufficient controls and methods, which would serve to strengthen their study results and conclusions. Here, we describe the application, utility, and interpretation of the suite of controls needed to make high quality qPCR and dPCR measurements of microorganisms in the environment. Our presentation is organized by the discrete steps and operations typical of this measurement process. We propose systematic terminology to minimize ambiguity and aid comparisons among studies. Example schemes for batching and combining controls for efficient work flow are demonstrated. We describe critical reporting elements for enhancing data credibility, and we provide an element checklist in the Supporting Information. Additionally, we present several key principles in metrology as context for laboratories to devise their own quality assurance and quality control reporting framework. Following the EMMI guidelines will improve comparability and reproducibility among qPCR and dPCR studies in environmental microbiology, better inform engineering and public health actions for preventing disease transmission through environmental pathways, and for the most pressing issues in the discipline, focus the weight of evidence in the direction toward solutions.

Occurrence and distributions of human-associated markers in an impacted urban watershed

Numerous genetic markers for microbial source tracking (MST) have been evaluated by testing a panel of target and nontarget faecal samples. However, the performance of MST markers may vary between faecal and water samples, thereby resulting in inaccurate water quality assessment. In this study, a 30-day sampling study was conducted in an urban river impacted by human- and sewage-associated pollution to evaluate the performance of different human-associated markers in environmental water. Additionally, marker decay was assessed via a microcosms approach. Overall, Bacteroidales 16sRNA and crAssphage markers exhibited higher prevalence in the study area, and their detection frequencies exceeded 90%. In contrast, Bacteroidales protein markers exhibited poor detection frequencies compared to other markers, with the prevalence of Hum2 and Hum163 reaching only 63% and 84%, respectively. Regarding marker abundance, there was no significant difference in the detection concentrations between Bacteroidales 16sRNA and crAssphage markers (p > 0.05); however, the concentrations of Bacteroidales protein markers were nearly 1 order of magnitude lower than those of other MST markers. The microcosm experiments indicated that the decay rate of crAssphage markers was significantly lower than that of other bacterial target markers, which may improve their detectability when the pollution source is located far from the sampling site. Due to the observed differences in performance and decay patterns among Bacteroidales 16sRNA, crAssphage, and Bacteroidales protein markers, we recommend the simultaneous use of multiple markers from different target microorganisms to obtain a more comprehensive understanding of the pollution sources. This approach would also provide an accurate assessment of pollution levels and health risks.

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.

Examining coastal dynamics and recreational water quality by quantifying multiple sewage specific markers in a North Carolina estuary

Fecal contamination is observed downstream of municipal separate storm sewer systems in coastal North Carolina. While it is well accepted that wet weather contributes to this phenomenon, less is understood about the contribution of the complex hydrology in this low-lying coastal plain. A quantitative microbial assessment was conducted in Beaufort, North Carolina to identify trends and potential sources of fecal contamination in stormwater receiving waters. Fecal indicator concentrations were significantly higher in receiving water downstream of a tidally submerged outfall compared to an outfall that was permanently submerged (p < 0.001), though tidal height was not predictive of human-specific microbial source tracking (MST) marker concentrations at the tidally submerged site. Short-term rainfall (i.e. <12 h) was predictive of E. coli, Enterococcus spp., and human-specific MST marker concentrations (Fecal Bacteroides, BacHum, and HF183) in receiving waters. The strong correlation between 12-hr antecedent rainfall and Enterococcus spp. (r = 0.57, p < 0.001, n = 92) suggests a predictive model could be developed based on rainfall to communicate risk for bathers. Additional molecular marker data indicates that the delivery of fecal sources is complex and highly variable, likely due to the influence of tidal influx (saltwater intrusion from the estuary) into the low-lying stormwater pipes. In particular, elevated MST marker concentrations (up to 2.56 × 10⁴ gene copies HF183/mL) were observed in standing water near surcharging street storm drain. These data are being used to establish a baseline for stormwater dynamics prior to dramatic rainfall in 2018 and to characterize the interaction between complex stormwater dynamics and water quality impairment in coastal NC.

Interlaboratory accuracy and precision among results of three sewage-associated marker genes in urban environmental estuarine waters and freshwater streams

The application of quantitative polymerase chain reaction (qPCR) based microbial source tracking (MST) marker genes are increasingly being used to identify contaminating sources and inform management decisions. In this study, we assessed interlaboratory agreement on duplicate environmental water samples collected from estuarine and freshwater locations, by comparing results of qPCR based testing for Bacteroides HF183, crAssphage CPQ_056, and pepper mild mottle virus (PMMoV). The overall agreements (co-detection and non-co-detection) between CSIRO Land and Water (CLW) laboratory and Sydney Water (SW) laboratory for the HF183, crAssphage CPQ_056 and PMMoV marker genes for duplicate water samples were 74, 75 and 74%, respectively. Cohene's kappa (k) revealed fair to moderate agreements and acceptable relative percent difference (RPD) values of <15% for duplicate samples. The pooled mean abundances of HF183, CPQ_056, and PMMoV in measurable samples at the CLW laboratory were 5.19 ± 0.93, 5.12 ± 0.82, and 4.42 ± 0.65 log₁₀ copies/L, respectively. However, the pooled mean abundances were significantly lower at the SW laboratory, HF183 (4.58 ± 0.84 log₁₀ copies/L), crAssphage CPQ_056 (4.20 ± 0.63 log₁₀ copies/L), and PMMoV (3.89 ± 0.41 log₁₀ copies/L). At individual sample level, most of the paired samples had <1 log₁₀ difference. Significant positive Spearman rank correlations were obtained between two laboratories for the HF183 (R_s = 0.65; p < 0.05), CPQ_056 (R_s = 0.79; p < 0.05), and PMMoV (R_s = 0.54; p < 0.05) marker genes. Several factors such as standards, qPCR platforms, PCR inhibitors, nucleic acid extraction efficiency and low levels of targets in some samples may have contributed to the observed discrepancies. Results presented in this study highlight the importance of standardized protocol, laboratory equipment (such as digital PCR), sample processing strategies and appropriate quality controls that may need implementation to further improve accuracy and precision of results between laboratories.

A comparison of E. coli concentration estimates quantified by the EPA and a Michigan laboratory network using EPA Draft Method C

We evaluated data from 10 laboratories that analyzed water samples from 82 recreational water sites across the state of Michigan between 2016 and 2018. Water sample replicates were analyzed by experienced U.S. Environmental Protection Agency (EPA) analysts and Michigan laboratories personnel, many of whom were newly trained, using EPA Draft Method C-a rapid quantitative polymerase chain reaction (qPCR) technique that provides same day Escherichia coli (E. coli) concentration results. Beach management decisions (i.e. remain open or issue an advisory or closure) based on E. coli concentration estimates obtained by Michigan labs and by the EPA were compared; the beach management decision agreed in 94% of the samples analyzed. We used the Wilcoxon one-sample signed rank test and nonparametric quantile regression to assess (1) the degree of agreement between E. coli concentrations quantified by Michigan labs versus the EPA and (2) Michigan lab E. coli measurement precision, relative to EPA results, in different years and water body types. The median quantile regression curve for Michigan labs versus EPA approximated the 1:1 line of perfect agreement more closely as years progressed. Similarly, Michigan lab E. coli estimates precision also demonstrated yearly improvements. No meaningful difference was observed in the degree of association between Michigan lab and EPA E. coli concentration estimates for inland lake and Great Lakes samples (median regression curve average slopes 0.93 and 0.95, respectively). Overall, our study shows that properly trained laboratory personnel can perform Draft Method C to a degree comparable with experienced EPA analysts. This allows health departments that oversee recreational water quality monitoring to be confident in qPCR results generated by the local laboratories responsible for analyzing the water samples.

Collection system investigation microbial source tracking (CSI-MST): Applying molecular markers to identify sewer infrastructure failures

Collection System Investigation Microbial Source Tracking (CSI-MST) is a novel, sensitive approach for identifying sewer infrastructure deficiencies using molecular markers. This method requires both a detailed understanding of collection and conveyance system infrastructure and quickly turned around molecular data to advise an adaptive, targeted in-pipe approach to detect deficiencies. Here we explain the CSI-MST approach and provide several case study examples of how this approach can be adapted to different scale watersheds to identify potential sewer infrastructure issues. This approach has been used to locate and confirm the remediation of numerous needed infrastructure repairs in the southeastern Virginia region. The selected case studies presented here serve as a proof of concept-this methodology can be adopted by other utilities and municipalities to address necessary wastewater infrastructure repairs in different regions.

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.

Microbial Indicators of Fecal Pollution: Recent Progress and Challenges in Assessing Water Quality

PURPOSE OF REVIEW

Fecal contamination of water is a major public health concern. This review summarizes recent developments and advancements in water quality indicators of fecal contamination.

RECENT FINDINGS

This review highlights a number of trends. First, fecal indicators continue to be a valuable tool to assess water quality and have expanded to include indicators able to detect sources of fecal contamination in water. Second, molecular methods, particularly PCR-based methods, have advanced considerably in their selected targets and rigor, but have added complexity that may prohibit adoption for routine monitoring activities at this time. Third, risk modeling is beginning to better connect indicators and human health risks, with the accuracy of assessments currently tied to the timing and conditions where risk is measured. Research has advanced although challenges remain for the effective use of both traditional and alternative fecal indicators for risk characterization, source attribution and apportionment, and impact evaluation.

Near real-time notification of water quality impairments in recreational freshwaters using rapid online detection of β-D-glucuronidase activity as a surrogate for Escherichia coli monitoring

Waterborne disease outbreaks associated with recreational waters continue to be reported around the world despite existing microbiological water quality monitoring frameworks. Most regulations resort to the use of culture-based enumeration of faecal indicator bacteria such as Escherichia coli to protect bathers from gastrointestinal illness risks. However, the long sample-to-result time of standard culture-based assays (minimum 18-24 h) and infrequent regulatory sampling (weekly or less) do not enable detection of episodic water quality impairments and associated public health risks. The objective of this study was to assess the suitability of an autonomous online technology measuring β-D-glucuronidase (GLUC) activity for near real-time monitoring of microbiological water quality in recreational waters and for the resulting beach management decisions. GLUC activity and E. coli concentrations were monitored at three freshwater sites in Quebec, Canada (sites Qc1-3) and one site in New Zealand (site NZ) between 2016 and 2018. We found site-dependent linear relationships between GLUC activity and E. coli concentrations and using confusion matrices, we developed site-specific GLUC activity beach action values (BAVs) matching the regulatory E. coli BAVs. Using the regulatory E. coli BAV as the gold standard, rates of false alarms (unnecessary beach advisories using GLUC activity BAV) and failures to act (failure to trigger advisories using GLUC activity) ranged between 0 and 32% and between 3 and 10%, respectively, which is comparable to the rates reported in other studies using qPCR-defined BAVs. However, a major benefit of the autonomous enzymatic technology is the real-time reporting of threshold exceedances, while temporal trends in GLUC activity can assist in understanding the underlying dynamics of faecal pollution and potential health risks. Our study is the first to describe the applicability of online near real-time monitoring of microbiological water quality as a tool for improved beach management and public health protection.

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.

Simplified Analysis of Measurement Data from A Rapid E. coli qPCR Method (EPA Draft Method C) Using A Standardized Excel Workbook

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

Ecological and Technical Mechanisms for Cross-Reaction of Human Fecal Indicators with Animal Hosts

Quantitative PCR (qPCR) assays for human/sewage marker genes have demonstrated sporadic positive results in animal feces despite their high specificities to sewage and human feces. It is unclear whether these positive reactions are caused by true occurrences of microorganisms containing the marker gene (i.e., indicator organisms) or nonspecific amplification (false positive). The distribution patterns of human/sewage indicator organisms in animals have not been explored in depth, which is crucial for evaluating a marker gene's true- or false-positive reactions. Here, we analyzed V6 region 16S rRNA gene sequences from 257 animal fecal samples and tested a subset of 184 using qPCR for human/sewage marker genes. Overall, specificities of human/sewage marker genes within sequencing data were 99.6% (BacV6-21), 96.9% (Lachno3), and 96.1% (HF183, indexed by its inferred V6 sequence). Occurrence of some true cross-reactions was associated with atypical compositions of organisms within the genera Blautia or Bacteroides For human/sewage marker qPCR assays, specificities were 96.7% (HF183/Bac287R), 96.2% (BacV6-21), 95.6% (human Bacteroides [HB]), and 94.0% (Lachno3). Select assays duplexed with either Escherichia coli or Enterococcus spp. were also validated. Most of the positive qPCR results in animals were low level and, on average, 2 orders of magnitude lower than the copy numbers of E. coli and Enterococcus spp. The lower specificity in qPCR assays compared to sequencing data was mainly caused by amplification of sequences highly similar to the marker gene and not the occurrence of the exact marker sequence in animal fecal samples.IMPORTANCE Identifying human sources of fecal pollution is critical to remediate sanitation concerns. Large financial investments are required to address these concerns; therefore, a high level of confidence in testing results is needed. Human fecal marker genes validated in this study showed high specificity in both sequencing data and qPCR results. Human marker sequences were rarely found in individual animals, and in most cases, the animals had atypical microbial communities. Sequencing also revealed the presence of closely related organisms that could account for nonspecific amplification in certain assays. Both the true cross-reactions and the nonspecific amplification had low signals well below E. coli or Enterococcus levels and likely would not impact the assay's ability to reliably detect human fecal pollution. No animal source had multiple human/sewage marker genes present; therefore, using a combination of marker genes would increase the confidence of human fecal pollution detection.

Assessing human-specific CrAssphage recovery after acidification-filtration concentrating method in environmental water

Pinpointing water pollution sources using host-specific gastrointestinal microbes, known as microbial source tracking (MST), have significant benefits for countries with water quality management issues related to pollution. A recently discovered bacteriophage, crAssphage, shows promise as a human-specific MST marker. However, loss of genetic materials during the recovery and the detection processes could alter the ability to measure virus quantities in a water sample. This study determined the crAssphage recovery efficiencies in water sources, including seawater, freshwater, and influent and effluent from a wastewater treatment plant, by spiking natural crAssphage concentrates prior to DNA extraction and quantitative PCR analysis. The results showed that river and seawater with no or low crAssphage background experienced no recovery loss. Evaluating recovery efficiencies in samples with high crAssphage backgrounds posed a challenge due to the inability to prepare high crAssphage titers. This study highlights the importance of intra-laboratory assessment of recovery efficiency in environmental samples for retrieving absolute crAssphage quantification with correction of bias among water samples and increase in data accuracy. PRACTITIONER POINTS: In laboratory assessment of recovery efficiency is crucial for bias correction and data accuracy for absolute crAssphage quantification in water samples. No loss in crAssphage recovery was observed in river and seawater that contained no or low crAssphage backgrounds. Inability to prepare high crAssphage spike concentrations remains the major limitation for evaluating recovery in samples with high crAssphage backgrounds. The results underline the importance of evaluating method recovery in real environmental samples that reflect actual matrix effect. Absolute crAssphage quantification, as human-specific pollution marker, could be used for prioritizing water quality restoration and area-based management plan.

A review on microbial contaminants in stormwater runoff and outfalls: Potential health risks and mitigation strategies

Demands on global water supplies are increasing in response to the need to provide more food, water, and energy for a rapidly growing population. These water stressors are exacerbated by climate change, as well as the growth and urbanisation of industry and commerce. Consequently, urban water authorities around the globe are exploring alternative water sources to meet ever-increasing demands. These alternative sources are primarily treated sewage, stormwater, and groundwater. Stormwater including roof-harvested rainwater has been considered as an alternative water source for both potable and non-potable uses. One of the most significant issues concerning alternative water reuse is the public health risk associated with chemical and microbial contaminants. Several studies to date have quantified fecal indicators and pathogens in stormwater. Microbial source tracking (MST) approaches have also been used to determine the sources of fecal contamination in stormwater and receiving waters. This review paper summarizes occurrence and concentrations of fecal indicators, pathogens, and MST marker genes in urban stormwater. A section of the review highlights the removal of fecal indicators and pathogens through water sensitive urban design (WSUD) or Best Management Practices (BMPs). We also discuss approaches for assessing and mitigating health risks associated with stormwater, including a summary of existing quantitative microbial risk assessment (QMRA) models for potable and non-potable reuse of stormwater. Finally, the most critical research gaps are identified for formulating risk management strategies.

Comparison of microbial source tracking efficacy for detection of cattle fecal contamination by quantitative PCR

Identification of fecal contamination sources in surface water has become heavily dependent on quantitative PCR (qPCR) because this technique allows for the rapid enumeration of fecal indicator bacteria as well as the detection and quantification of fecal source-associated genetic markers in the environment. Identification of contamination sources in impaired waters is a prerequisite for developing best management practices to reduce future pollution. Proper management decisions rely on the quality and interpretation of qPCR data. In this study, we developed a method to determine analytical and process lower limits of detection (LLOD) and quantification (LLOQ) using two cattle-associated genetic markers targeting Bacteroidales. Analytical LLOD (A_LLOD) for both CowM2 and CowM3 genetic markers in the qPCR assay were five gene copies per reaction. Using composite fecal DNA, the analytical LLOQ (A_LLOQ) determined for CowM2 and CowM3 were 78 and 195 gene copies/reaction, respectively. When plasmid DNA was used, the A_LLOQ for CowM2 and CowM3 were 46 and 20 gene copies/reaction, respectively. The process LLOD (P_LLOD) for CowM2 and CowM3 were 0.4 and 0.02 mg feces/filter (wet weight), respectively. Using the standard deviation value of 0.25 as a cut-off point for LLOQ in regression analysis, the process LLOQ (P_LLOQ) for CowM2 and CowM3 were 3.2 and 0.3 mg feces/filter, respectively. These results indicate that CowM3 exhibited superior performance characteristics compared with CowM2 for fecal samples collected from our geographical region. Moreover, the method for calculating LLOD and LLOQ developed here can be applied to other microbial source tracking studies.

Variably improved microbial source tracking with digital droplet PCR

This study addressed whether digital droplet PCR (ddPCR) could improve sensitivity and specificity of human-associated Bacteroidales genetic markers, BacHum and B. theta, and their quantification in environmental and fecal composite samples. Human markers were quantified by qPCR and ddPCR platforms obtained from the same manufacturer. A total of 180 samples were evaluated by each platform including human and animal feces, sewage, and environmental water. The sensitivity of ddPCR and qPCR marker assays in sewage and human stool was 0.85-1.00 with marginal reduction in human stool by ddPCR relative to qPCR (<10%). The prevalence and distribution of markers across complex sample types was similar (74-100% agreement) by both platforms with qPCR showing higher sensitivity for markers in environmental and composite samples and ddPCR showing greater reproducibility for marker detection in fecal composites. Determination of BacHum prevalence in fecal samples by ddPCR increased specificity relative to qPCR (from 0.58 to 0.88) and accuracy (from 0.77 to 0.94), while the B. theta assay performed similarly on both platforms (specificity = 0.98). In silico analysis indicated higher specificity of ddPCR for BacHum was not solely attributed to reduced sensitivity relative to qPCR. Marker concentrations measured by ddPCR for all sample types were consistently lower than those measured by qPCR, by a factor of 2.6 ± 2.8 for B. theta and 18.7 ± 10.0 for BacHum. We suggest that differences in assay performance on ddPCR and qPCR platforms may be linked to the characteristics of the assay targets (that is, genes with multiple versus single copies and encoding proteins versus ribosomal RNA) however further work is needed to validate these ideas. We conclude that ddPCR is a suitable tool for microbial source tracking, however, other factors such as cost-effectiveness and assay-specific performance should be considered.

Advancements in mitigating interference in quantitative polymerase chain reaction (qPCR) for microbial water quality monitoring

The United States Environmental Protection Agency's (EPA)¹ 2012 Recreational Water Quality Criteria included an Enterococcus spp. quantitative polymerase chain reaction (qPCR) method as a supplemental indicator-method. In 2012, performance of qPCR for beach monitoring remained limited, specifically with addressing interference. A systematic literature search of peer-reviewed publications was conducted to identify where Enterococcus spp. and E. coli qPCR methods have been applied in ambient waters. In the present study, we evaluated interference rates, contributing factors resulting in increased interference in these methods, and method improvements that reduced interference. Information on qPCR methods of interest and interference controls were reported in 16 papers for Enterococcus spp. and 13 papers for E. coli. Of the Enterococcus spp. qPCR methods assessed in this effort, the lowest frequencies of interference were reported in samples using Method 1609. Low frequencies of sample interference were also reported EPA's modified E. coli qPCR method, which incorporates the same reagents and interference controls as Method 1609. The literature indicates that more work is needed to demonstrate the utility of E. coli qPCR for widespread beach monitoring purposes, whereas more broad use of Method 1609 for Enterococcus spp. is appropriate when the required and suggested controls are employed.

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.

Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C)

There is interest in the application of rapid quantitative polymerase chain reaction (qPCR) methods for recreational freshwater quality monitoring of the fecal indicator bacteria Escherichia coli (E. coli). In this study we determined the performance of 21 laboratories in meeting proposed, standardized data quality acceptance (QA) criteria and the variability of target gene copy estimates from these laboratories in analyses of 18 shared surface water samples by a draft qPCR method developed by the U.S. Environmental Protection Agency (EPA) for E. coli. The participating laboratories ranged from academic and government laboratories with more extensive qPCR experience to "new" water quality and public health laboratories with relatively little previous experience in most cases. Failures to meet QA criteria for the method were observed in 24% of the total 376 test sample analyses. Of these failures, 39% came from two of the "new" laboratories. Likely factors contributing to QA failures included deviations in recommended procedures for the storage and preparation of reference and control materials. A master standard curve calibration model was also found to give lower overall variability in log₁₀ target gene copy estimates than the delta-delta Ct (ΔΔCt) calibration model used in previous EPA qPCR methods. However, differences between the mean estimates from the two models were not significant and variability between laboratories was the greatest contributor to overall method variability in either case. Study findings demonstrate the technical feasibility of multiple laboratories implementing this or other qPCR water quality monitoring methods with similar data quality acceptance criteria but suggest that additional practice and/or assistance may be valuable, even for some more generally experienced qPCR laboratories. Special attention should be placed on providing and following explicit guidance on the preparation, storage and handling of reference and control materials.

Standardized data quality acceptance criteria for a rapid Escherichia coli qPCR method (Draft Method C) for water quality monitoring at recreational beaches

There is growing interest in the application of rapid quantitative polymerase chain reaction (qPCR) and other PCR-based methods for recreational water quality monitoring and management programs. This interest has strengthened given the publication of U.S. Environmental Protection Agency (EPA)-validated qPCR methods for enterococci fecal indicator bacteria (FIB) and has extended to similar methods for Escherichia coli (E. coli) FIB. Implementation of qPCR-based methods in monitoring programs can be facilitated by confidence in the quality of the data produced by these methods. Data quality can be determined through the establishment of a series of specifications that should reflect good laboratory practice. Ideally, these specifications will also account for the typical variability of data coming from multiple users of the method. This study developed proposed standardized data quality acceptance criteria that were established for important calibration model parameters and/or controls from a new qPCR method for E. coli (EPA Draft Method C) based upon data that was generated by 21 laboratories. Each laboratory followed a standardized protocol utilizing the same prescribed reagents and reference and control materials. After removal of outliers, statistical modeling based on a hierarchical Bayesian method was used to establish metrics for assay standard curve slope, intercept and lower limit of quantification that included between-laboratory, replicate testing within laboratory, and random error variability. A nested analysis of variance (ANOVA) was used to establish metrics for calibrator/positive control, negative control, and replicate sample analysis data. These data acceptance criteria should help those who may evaluate the technical quality of future findings from the method, as well as those who might use the method in the future. Furthermore, these benchmarks and the approaches described for determining them may be helpful to method users seeking to establish comparable laboratory-specific criteria if changes in the reference and/or control materials must be made.

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.

Human and animal microbial source tracking in a tropical river with multiple land use activities

The enhancement and restoration of the water quality of deteriorating surface water resources can be challenging, particularly for rivers with multiple usages, such as agriculture, animal husbandry, human residence, and industries. Recently, the performance of DNA-based microbial source tracking (MST) indicators detected by end-point and quantitative PCR assays for identifying sources of fecal pollution from human sewage, swine, and cattle and non-host-specific (universal) fecal pollution in the Tha Chin River basin, Thailand, was evaluated. The present study monitored these validated MST markers and various physicochemical and microbial water quality parameters in samples collected from twelve stations along the Tha Chin River during four sampling events in the wet and dry seasons. No significant difference in precipitation was observed between the wet and dry samplings. Universal markers (both PCR and qPCR) were detected in all 48 samples, indicating persistent and continuing fecal contamination. The sewage- and swine-specific qPCR marker concentrations did not vary among the sampling events, whereas cattle-specific qPCR markers were detected only in the wet season. Animal-specific markers were detected in the lower Tha Chin River section, which is characterized by intensive animal farming. Sewage-specific markers were also found in the lower section and near an upstream residential area. The high agreement (87.5-100%) between the PCR and qPCR results suggested that PCR could serve as a lower-cost MST screening test that requires less technical expertise. A multivariate analysis conducted using the survival analysis procedure to include censored data also emphasized the high pollution in the lower section of the river at all sampling events. Universal and swine-specific markers showed moderate correlations with microbial indicators, including total coliforms, fecal coliforms, E. coli, and enterococci. None of the MST markers or microbial parameters were associated with the measured physicochemical parameters. This study provides the first evaluation of MST markers for monitoring surface freshwater in Thailand, and the findings might aid the pollution surveillance of impaired water bodies and the development of strategies for improving their water quality.

Canonical Variable Selection for Ecological Modeling of Fecal Indicators

More than 270,000 km of rivers and streams are impaired due to fecal pathogens, creating an economic and public health burden. Fecal indicator organisms such as are used to determine if surface waters are pathogen impaired, but they fail to identify human health risks, provide source information, or have unique fate and transport processes. Statistical and machine learning models can be used to overcome some of these weaknesses, including identifying ecological mechanisms influencing fecal pollution. In this study, canonical correlation analysis (CCorA) was performed to select parameters for the machine learning model, Maxent, to identify how chemical and microbial parameters can predict impairment and F-somatic bacteriophage detections. Models were validated using a bootstrapping cross-validation. Three suites of models were developed; initial models using all parameters, models using parameters identified in CCorA, and optimized models after further sensitivity analysis. Canonical correlation analysis reduced the number of parameters needed to achieve the same degree of accuracy in the initial model (84.7%), and sensitivity analysis improved accuracy to 86.1%. Bacteriophage model accuracies were 79.2, 70.8, and 69.4% for the initial, CCorA, and optimized models, respectively; this suggests complex ecological interactions of bacteriophages are not captured by CCorA. Results indicate distinct ecological drivers of impairment depending on the fecal indicator organism used. impairment is driven by increased hardness and microbial activity, whereas bacteriophage detection is inhibited by high levels of coliforms in sediment. Both indicators were influenced by organic pollution and phosphorus limitation.

Quantification of plasmid DNA standards for U.S. EPA fecal indicator bacteria qPCR methods by droplet digital PCR analysis

An obstacle to establishing widely useful data acceptance criteria for U.S. Environmental Protection Agency (EPA) qPCR methods has been the unavailability of standardized reference materials. Earlier versions of EPA Methods 1609 and 1611 for enterococci used cellular reference materials for quantifying enterococci in unknown test samples, however, EPA updates to these fundamentally DNA-based analysis methods have shifted toward the use of DNA standards. This report describes the application of droplet digital PCR (ddPCR) analysis for the quantification of a set of synthetic plasmid DNA standards that have been made available for updated EPA Methods 1609.1 and 1611.1 as well as for EPA Draft Method C for Escherichia coli. To obtain the most accurate concentration estimates possible, part of this effort was to develop a data analysis model for determining the fluorescence thresholds that distinguish positive from negative droplets produced by the ddPCR reactions. Versions of this model are described for applications with individual reactions, multiple reactions within a ddPCR system run, and multiple reactions within and across different system runs. The latter version was applied toward determinations of error in the concentration estimates of the standards from replicate analyses of each standard in multiple ddPCR system runs. Mean concentration estimates for the five standards from the ddPCR analyses were 4.356, 3.381, 2.371, 1.641 and 1.071 log₁₀ copies/5 μL with associated standard deviations of 0.074, 0.082, 0.108, 0.131 and 0.188, respectively. These estimates contrasted with expected log₁₀ concentrations of 4.6, 3.6, 2.6, 1.9 and 1.3 copies/5 μL, respectively, based on the yield of the plasmid reported by the vendor and spectrophotometric analysis of the initial stock solution of this material. These results illustrate how the analyses of original stocks may lead to potential bias(es) in the concentration estimates of final DNA standards and subsequently in the estimates of unknown test samples determined from these standards in qPCR analyses.

Toward Forensic Uses of Microbial Source Tracking

The science of microbial source tracking has allowed researchers and watershed managers to go beyond general indicators of fecal pollution in water such as coliforms and enterococci, and to move toward an understanding of specific contributors to water quality issues. The premise of microbial source tracking is that characteristics of microorganisms that are strongly associated with particular host species can be used to trace fecal pollution to particular animal species (including humans) or groups, e.g., ruminants or birds. Microbial source tracking methods are practiced largely in the realm of research, and none are approved for regulatory uses on a federal level. Their application in the conventional sense of forensics, i.e., to investigate a crime, has been limited, but as some of these methods become standardized and recognized in a regulatory context, they will doubtless play a larger role in applications such as total maximum daily load assessment, investigations of sewage spills, and contamination from agricultural practices.

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.

Regional Assessment of Human Fecal Contamination in Southern California Coastal Drainages

Host-associated genetic markers that allow for fecal source identification have been used extensively as a diagnostic tool to determine fecal sources within watersheds, but have not been used in routine monitoring to prioritize remediation actions among watersheds. Here, we present a regional assessment of human marker prevalence among drainages that discharge to the U.S. southern California coast. Approximately 50 samples were analyzed for the HF183 human marker from each of 22 southern California coastal drainages under summer dry weather conditions, and another 50 samples were targeted from each of 23 drainages during wet weather. The HF183 marker was ubiquitous, detected in all but two sites in dry weather and at all sites during wet weather. However, there was considerable difference in the extent of human fecal contamination among sites. Similar site ranking was produced regardless of whether the assessment was based on frequency of HF183 detection or site average HF183 concentration. However, site ranking differed greatly between dry and wet weather. Site ranking also differed greatly when based on enterococci, which do not distinguish between pollution sources, vs. HF183, which distinguishes higher risk human fecal sources from other sources, indicating the additional value of the human-associated marker as a routine monitoring tool.

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.

Detection of Antibiotic Resistance Genes in Source and Drinking Water Samples from a First Nations Community in Canada

Access to safe drinking water is now recognized as a human right by the United Nations. In developed countries like Canada, access to clean water is generally not a matter of concern. However, one in every five First Nations reserves is under a drinking water advisory, often due to unacceptable microbiological quality. In this study, we analyzed source and potable water from a First Nations community for the presence of coliform bacteria as well as various antibiotic resistance genes. Samples, including those from drinking water sources, were found to be positive for various antibiotic resistance genes, namely, ampC, tet(A), mecA, β-lactamase genes (SHV-type, TEM-type, CTX-M-type, OXA-1, and CMY-2-type), and carbapenemase genes (KPC, IMP, VIM, NDM, GES, and OXA-48 genes). Not surprisingly, substantial numbers of total coliforms, including Escherichia coli, were recovered from these samples, and this result was also confirmed using Illumina sequencing of the 16S rRNA gene. These findings deserve further attention, as the presence of coliforms and antibiotic resistance genes potentially puts the health of the community members at risk.

IMPORTANCE

In this study, we highlight the poor microbiological quality of drinking water in a First Nations community in Canada. We examined the coliform load as well as the presence of antibiotic resistance genes in these samples. This study examined the presence of antibiotic-resistant genes in drinking water samples from a First Nations Community in Canada. We believe that our findings are of considerable significance, since the issue of poor water quality in First Nations communities in Canada is often ignored, and our findings will help shed some light on this important issue.