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

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.

A one health approach for monitoring antimicrobial resistance: developing a national freshwater pilot effort

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

Integrating molecular microbial methods to improve faecal pollution management in rivers with designated bathing waters

Rivers are at risk from a variety of pollution sources. Faecal pollution is of particular concern since it disperses pathogenic microorganisms in the aquatic environment. Currently, faecal pollution levels in rivers is monitored using faecal indicator bacteria (FIB) that do not offer information about pollution sources and associated risks. This study used a combined molecular approach, along with measurements of water quality, to gain information on pollution sources, and risk levels, in a newly designated recreational bathing site in the River Wharfe (UK). Physico-chemical parameters were monitored in situ, with water quality multiparameter monitoring sondes installed during the 2021 bathing season. The molecular approach was based on quantitative PCR (qPCR)-aided Microbial Source Tracking (MST) and 16S rRNA gene metabarcoding to obtain a fingerprint of bacterial communities and identify potential bioindicators. The analysis from the water quality sondes showed that ammonium was the main parameter determining the distribution of FIB values. Lower faecal pollution levels were detected in the main river when compared to tributaries, except for samples in the river located downstream of a wastewater treatment plant. The faecal pollution type (anthropogenic vs. zoogenic) changed the diversity and the structure of bacterial communities, giving a distinctive fingerprint that can be used to inform source. DNA-based methods showed that the presence of human-derived bacteria was associated with Escherichia coli spikes, coinciding with higher bacterial diversity and the presence of potential pathogenic bacteria mainly of the genus Mycobacterium, Aeromonas and Clostridium. Samples collected after a heavy rainfall event were associated with an increase in Bacteroidales, which are markers of faecal pollution, including Bacteroides graminisolvens, a ruminant marker associated with surface run-off from agricultural sources. The combined use of qPCR and 16S rRNA sequencing was able to identify pollution sources, and novel bacterial indicators, thereby aiding decision-making and management strategies in recreational bathing rivers.

Investigating the Relationship between Surface Water Pollution and Onsite Wastewater Treatment Systems

Onsite wastewater treatment systems (OWTSs) are important nonpoint sources (NPSs) of pollution to consider in watershed management. However, limited OWTS data availability makes it challenging to account for them as an NPS of water pollution. In this study, we succeeded in obtaining OWTS permits and integrated them with environmental data to model the pollution potential from OWTSs at the watershed scale using GIS-based multicriteria decision analysis. Then, in situ water quality parameters─Escherichia coli (E. coli), total nitrogen, total phosphorus, temperature, and pH─were measured along the main tributary at base-flow conditions. Three general linear models were developed to relate E. coli to water quality parameters and OWTS pollution indicators. It was found that the model with the OWTS pollution potential had the lowest corrected Akaike information criterion (AICc) value (35.01) compared to the models that included classified OWTS pollution potential input criteria (AICc = 36.76) and land cover (AICc = 36.74). These results demonstrate that OWTSs are a significant contributor to surface water pollution, and future efforts should be made to improve access to OWTS data (i.e., location and age) to account for these systems as an NPS of water pollution.

Systematic tracing of nitrate sources in a complex river catchment: An integrated approach using stable isotopes and hydrological models

Quantitative estimation for tracking the transport of various nitrate sources is required to effectively manage nitrate loading in complex river systems. In this study, we validated an integrated framework using field isotopic data (δ¹⁵N_NO3 and δ¹⁸O_NO3) of nitrates and hydrological modeling (hydrological simulation program FORTRAN; HSPF) to determine anthropogenic nitrate flux among different land-use types within a watershed. Nitrate isotopic compositions showed different ranges among four land-use types (4.9 to 15.5‰ for δ¹⁵N_NO3, -4.9 to 12.1‰ for δ¹⁸O_NO3), reflecting the different nitrate sources (sewage, synthetic fertilizer, effluent and soil) within watersheds. Based on the integration of HSPF modeling, we also found that total nitrate loads might be partially controlled by hydrological conditions such as water discharge (12,040.3-22,793.2 L/s) from upstream to downstream. Among the nitrate sources, the sewage transport showed unique enhancement near urban boundaries, along with an increase in total nitrate load (>193.5 NO₃-N g/s km²) in downstream areas. In addition, the isotopic- and model-based nitrate fluxes showed good correlation for urban sources (R²=0.73, p < 0.05) but poor correlations for agriculture-dominated land use (R²=0.13, p > 0.05), reflecting the potential influence of surface runoff and ground infiltration into the watershed. Consequently, this research provided useful information to establish nitrogen management policy controlling point and non-point nitrate source loads in various land-use types for the restoration of water quality and aquatic ecosystem in the complex river system. Considering the recent increase in human activities near aquatic environments, this framework would be effective for individually estimating the quantitative contributions of anthropogenic nitrate sources transported along river-coastal systems.

Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk-Based Screening Techniques

In a study of 44 diverse sampling sites across 16 Great Lakes tributaries, 110 pharmaceuticals were detected of 257 monitored. The present study evaluated the ecological relevance of detected chemicals and identified heavily impacted areas to help inform resource managers and guide future investigations. Ten pharmaceuticals (caffeine, nicotine, albuterol, sulfamethoxazole, venlafaxine, acetaminophen, carbamazepine, gemfibrozil, metoprolol, and thiabendazole) were distinguished as having the greatest potential for biological effects based on comparison to screening-level benchmarks derived using information from two biological effects databases, the ECOTOX Knowledgebase and the ToxCast database. Available evidence did not suggest substantial concern for 75% of the monitored pharmaceuticals, including 147 undetected pharmaceuticals and 49 pharmaceuticals with screening-level alternative benchmarks. However, because of a lack of biological effects information, screening values were not available for 51 detected pharmaceuticals. Samples containing the greatest pharmaceutical concentrations and having the highest detection frequencies were from Lake Erie, southern Lake Michigan, and Lake Huron tributaries. Samples collected during low-flow periods had higher pharmaceutical concentrations than those collected during increased-flow periods. The wastewater-treatment plant effluent content in streams correlated positively with pharmaceutical concentrations. However, deviation from this correlation demonstrated that secondary factors, such as multiple pharmaceutical sources, were likely present at some sites. Further research could investigate high-priority pharmaceuticals as well as those for which alternative benchmarks could not be developed. Environ Toxicol Chem 2022;41:2221-2239. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Detangling Seasonal Relationships of Fecal Contamination Sources and Correlates with Indicators in Michigan Watersheds

Despite the widely acknowledged public health impacts of surface water fecal contamination, there is limited understanding of seasonal effects on (i) fate and transport processes and (ii) the mechanisms by which they contribute to water quality impairment. Quantifying relationships between land use, chemical parameters, and fecal bacterial concentrations in watersheds can help guide the monitoring and control of microbial water quality and explain seasonal differences. The goals of this study were to (i) identify seasonal differences in Escherichia coli and Bacteroides thetaiotaomicron concentrations, (ii) evaluate environmental drivers influencing microbial contamination during baseflow, snowmelt, and summer rain seasons, and (iii) relate seasonal changes in B. thetaiotaomicron to anticipated gastrointestinal infection risks. Water chemistry data collected during three hydroclimatic seasons from 64 Michigan watersheds were analyzed using seasonal linear regression models with candidate variables including crop and land use proportions, prior precipitation, chemical parameters, and variables related to both wastewater treatment and septic usage. Adaptive least absolute shrinkage and selection operator (LASSO) linear regression with bootstrapping was used to select explanatory variables and estimate coefficients. Regardless of season, wastewater treatment plant and septic system usage were consistently selected in all primary models for B. thetaiotaomicron and E. coli. Chemistry and precipitation-related variable selection depended upon season and organism. These results suggest a link between human pollution (e.g., septic systems) and microbial water quality that is dependent on flow regime.

IMPORTANCE In this study, a data set of 64 Michigan watersheds was utilized to gain insights into fecal contamination sources, drivers, and chemical correlates across seasons for general E. coli and human-specific fecal indicators. Results reaffirmed a link between human-specific sources (e.g., septic systems) and microbial water quality. While the importance of human sources of fecal contamination and fate and transport variables (e.g., precipitation) remain important across seasons, this study provides evidence that fate and transport mechanisms vary with seasonal hydrologic condition and microorganism source. This study contributes to a body of research that informs prioritization of fecal contamination source control and surveillance strategy development to reduce the public health burden of surface water fecal contamination.

Vitellogenin Induction in Mucus from Brook Trout (Salvelinus fontinalis)

Induction of vitellogenin (VTG) is widely used as a biomarker of exposure of male or immature fish to chemicals that are agonists of the estrogen receptor (i.e., xenoestrogens). Analysis of VTG in samples of epidermal mucosa collected from fish is a non-invasive method for evaluating whether wild fish are exposed to xenoestrogens. In this study, the mean levels of VTG in the mucus of immature brook trout (Salvelinus fontinalis) collected from the Credit River in Ontario, Canada downstream of aging residential septic systems and in an agricultural watershed were 0.67 ng per mg protein, which was significantly elevated relative to the mean VTG levels of 0.22 ng per mg protein in the mucus of immature brook trout collected from a less impacted site. To validate the mucus assay, immature brook trout were exposed in the laboratory to 17α-ethinylestradiol (EE2) at nominal concentrations of 10, 50 and 100 ng/L and VTG levels in mucus from these fish showed a concentration-dependent increase relative to fish from the control treatment. This study illustrates the utility of this non-lethal method for assessing whether wild fish have been exposed in situ to xenoestrogens. Exposures to xenoestrogens from non-point sources may be impacting brook trout populations in urban watersheds in southern Ontario.

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework

Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water. Thus, we implemented the newly developed microbial find, inform, and test framework to identify spatial sources and their impacts on human (HuBac) and bovine (BoBac) MST markers, quantified from both riverbed sediment and surface water in a bovine-dense region. Dairy feeding operations and low-intensity developed land-cover were associated with 99% (p-value < 0.05) and 108% (p-value < 0.05) increases, respectively, in the relative abundance of BoBac in sediment, and with 79% (p-value < 0.05) and 39% increases in surface water. Septic systems were associated with a 48% increase in the relative abundance of HuBac in sediment and a 56% increase in surface water. Stronger source signals were observed for sediment responses compared to water. By defining source locations, predicting river impacts, and estimating source influence ranges in a Great Lakes region, this work informs pollution mitigation strategies of local and global significance.

Incidence of human associated HF183 Bacteroides marker and E. coli levels in New Orleans Canals

With a focus on five sites in an impaired, densely populated area in the New Orleans area, we investigated the temporal and spatial variability of standard FIB and a marker of human-associated pollution (Bacteroides HF183). With all sites combined, only a weak positive correlation (r = 0.345; p = 0.001) was observed between E. coli and HF183. Also, specific conductivity (r = - 0.374; p < 0.0001) and dissolved oxygen (r = - 0.390; p < 0.0001) were observed to show a weak moderate correlation with E. coli. These correlations increased to moderately negative when HF183 was correlated with specific conductivity (r = - 0.448; p < 0.0001) and dissolved oxygen (r = - 0.455; p < 0.0001). E. coli contamination was generally highest at the sites in the canal that are situated in the most densely populated part of the watershed while HF183 was frequently detected across all sites. E. coli concentrations were significantly higher (p < 0.05) when HF183 was present. HF183 was detected at significantly higher concentrations in samples that exceeded the EPA water quality standard (WQS) than those that did not (p < 0.05). Dissolved oxygen and specific conductivity were significantly lower when E. coli WQS was exceeded or when HF183 was present (p < 0.05). Rainfall impacted E. coli concentrations and HF183 differently at the study sites. While HF183 and E. coli concentrations levels were significantly higher (p < 0.05) if the days prior to sampling had been wet, the frequency of detection of HF183 was unimpacted, as comparable detection rates were recorded during wet and dry weather conditions. Without testing for HF183, it would have been assumed, based on testing for E. coli alone, that human fecal pollution was only associated with densely populated areas and rainfall events. E. coli alone may not be an effective indicator of sewage pollution at the study sites across all weather conditions and may need to be complemented with HF183 enumeration to optimize human fecal pollution identification and management at the watershed level.

Nitrate sources and transformations in surface water of a mining area due to intensive mining activities: Emphasis on effects on distinct subsidence waters

The increase in NO₃^- content in surface water caused by intensive mining activities in Huainan City, China, has attracted considerable attention owing to the deterioration of water quality and the degradation of ecosystems in recent years. The Huainan mining area, which is highly disturbed by anthropogenic activities, was selected as a typical observation area, and the surface water was classified as open subsidence water (OSW), closed subsidence water (CSW), and river water (RW). Moreover, the hydrochemical parameters and the δ¹⁵N and δ¹⁸O values of nitrate were employed to quantitatively trace the sources and biochemical transformation of NO₃^-, and the contribution ratios of different NO₃^- sources were estimated using the stable isotope analysis in R based on the Bayesian model. There was evident nitrification in the study area, but no significant denitrification has occurred. A substantial portion of δ¹⁵N-NO₃^- demonstrated complex sources of NO₃^-. Compared with those of CSW, the NO₃^- compositions of the OSW approached to those of the RW due to river recharge and discharge, and were greatly affected by anthropogenic activities. The proportional contribution of manure and sewage in the OSW was found to be the highest with a mean value of 39.5 % ± 12.3 %, which was followed by that of mine drainage (mean: 22.1 % ± 13.1 %), chemical fertilizer (mean: 17.5 % ± 10.6 %), and soil organic nitrogen (mean: 17.5 % ± 11.6 %). In the RW, the highest mean contribution of manure sewage was 35.2 % ± 9.7 %, which was followed by that of chemical fertilizer (mean: 29.3 % ± 7.2 %), mine drainage (mean: 23.4 % ± 13.0 %), and soil organic nitrogen (mean: 10.9 % ± 8.3 %). In contrast, the contribution of chemical fertilizer to the CSW was the highest with a mean value of 33.9 % ± 13.6 %, which was followed by that of soil organic nitrogen (mean: 26.5 % ± 13.8 %), mine drainage (mean: 18.1 % ± 11.6 %). Therefore, NO₃^- in the surface water of the mining area primarily originates from chemical fertilizers and manure sewage. In addition, the contribution of mine drainage to nitrate in the study area indicates the potential impact of mining activities on surface water. These findings highlight the value of classifying different types of surface water in tracing NO₃^- contamination sources, and provide relevant theoretical basis for tracing nitrate sources in other areas.

Tracking Major Sources of Water Contamination Using Machine Learning

Current microbial source tracking techniques that rely on grab samples analyzed by individual endpoint assays are inadequate to explain microbial sources across space and time. Modeling and predicting host sources of microbial contamination could add a useful tool for watershed management. In this study, we tested and evaluated machine learning models to predict the major sources of microbial contamination in a watershed. We examined the relationship between microbial sources, land cover, weather, and hydrologic variables in a watershed in Northern California, United States. Six models, including K-nearest neighbors (KNN), Naïve Bayes, Support vector machine (SVM), simple neural network (NN), Random Forest, and XGBoost, were built to predict major microbial sources using land cover, weather and hydrologic variables. The results showed that these models successfully predicted microbial sources classified into two categories (human and non-human), with the average accuracy ranging from 69% (Naïve Bayes) to 88% (XGBoost). The area under curve (AUC) of the receiver operating characteristic (ROC) illustrated XGBoost had the best performance (average AUC = 0.88), followed by Random Forest (average AUC = 0.84), and KNN (average AUC = 0.74). The importance index obtained from Random Forest indicated that precipitation and temperature were the two most important factors to predict the dominant microbial source. These results suggest that machine learning models, particularly XGBoost, can predict the dominant sources of microbial contamination based on the relationship of microbial contaminants with daily weather and land cover, providing a powerful tool to understand microbial sources in water.

Combining multi-isotopic and molecular source tracking methods to identify nitrate pollution sources in surface and groundwater

Nitrate (NO₃^-) pollution adversely impacts surface and groundwater quality. In recent decades, many countries have implemented measures to control and reduce anthropogenic nitrate pollution in water resources. However, to effectively implement mitigation measures at the origin of pollution,the source of nitrate must first be identified. The stable nitrogen and oxygen isotopes of NO₃^- (ẟ¹⁵N and ẟ¹⁸O) have been widely used to identify NO₃^- sources in water, and their combination with other stable isotopes such as boron (ẟ¹¹B) has further improved nitrate source identification. However, the use of these datasets has been limited due to their overlapping isotopic ranges, mixing between sources, and/or isotopic fractionation related to physicochemical processes. To overcome these limitations, we combined a multi-isotopic analysis with fecal indicator bacteria (FIB) and microbial source tracking (MST) techniques to improve nitrate origin identification. We applied this novel approach on 149 groundwater and 39 surface water samples distributed across Catalonia (NE Spain). A further 18 wastewater treatment plant (WWTP) effluents were also isotopically and biologically characterized. The groundwater and surface water results confirm that isotopes and MST analyses were complementary and provided more reliable information on the source of nitrate contamination. The isotope and MST data agreed or partially agreed in most of the samples evaluated (79 %). This approach was especially useful for nitrate pollution tracing in surface water but was also effective in groundwater samples influenced by organic nitrate pollution. Furthermore, the findings from the WWTP effluents suggest that the use of literature values to define the isotopic ranges of anthropogenic sources can constrain interpretations. We therefore recommend that local sources be isotopically characterized for accurate interpretations. For instance, the detection of MST inferred animal influence in some WWTP effluents, but the ẟ¹¹B values were higher than those reported in the literature for wastewater. The results of this study have been used by local water authorities to review uncertain cases and identify new vulnerable zones in Catalonia according to the European Nitrate Directive (91/676/CEE).

Implementation and integration of microbial source tracking in a river watershed monitoring plan

Fecal pollution of water bodies poses a serious threat for public health and ecosystems. Microbial source tracking (MST) is used to track the source of this pollution facilitating better management of pollution at the source. In this study we tested 12 MST markers to track human, ruminant, sheep, horse, pig and gull pollution to assess their usefulness as an effective management tool of water quality. First, the potential of the selected markers to track the source was evaluated using fresh fecal samples. Subsequently, we evaluated their performance in a catchment with different impacts, considering land use and environmental conditions. All MST markers showed high sensitivity and specificity, although none achieved 100% for both. Although some of the MST markers were detected in hosts other than the intended ones, their abundance in the target group was always several orders of magnitude higher than in the non-target hosts, demonstrating their suitability to distinguish between sources of pollution. The MST analysis matched the land use in the watershed allowing an accurate assessment of the main sources of pollution, in this case mainly human and ruminant pollution. Correlating environmental parameters including temperature and rainfall with MST markers provided insight into the dynamics of the pollution in the catchment. The levels of the human marker showed a significant negative correlation with rainfall in human polluted areas suggesting a dilution of the pollution, whereas at agricultural areas the ruminant marker increased with rainfall. There were no seasonal differences in the levels of human marker, indicating human pollution as a constant pressure throughout the year, whereas the levels of the ruminant marker was influenced by the seasons, being more abundant in summer and autumn. MST analysis integrated with land use and environmental data can improve the management of fecal polluted areas and set up best practice.

Microbial source tracking (MST) in Chattahoochee River National Recreation Area: Seasonal and precipitation trends in MST marker concentrations, and associations with E. coli levels, pathogenic marker presence, and land use

Escherichia coli levels in recreational waters are often used to predict when fecal-associated pathogen levels are a human health risk. The reach of the Chattahoochee River that flows through the Chattahoochee River National Recreation Area (CRNRA), located in the Atlanta-metropolitan area, is a popular recreation area that frequently exceeds the U.S. Environmental Protection Agency beach action value (BAV) for E. coli. A BacteriALERT program has been implemented to provide real-time E. coli estimates in the reach and notify the public of potentially harmful levels of fecal-associated pathogens as indicated by surrogate models based on real-time turbidity measurements from continuous water quality monitoring stations. However, E. coli does not provide information about the sources of fecal contamination and its accuracy as a human health indicator is questionable when sources of contamination are non-human. The objectives of our study were to investigate, within the Park and surrounding watersheds, seasonal and precipitation-related patterns in microbial source tracking marker concentrations of possible sources (human, dog, and ruminant), assess correlations between source contamination levels and culturable E. coli levels, determine which sources best explained model-based E. coli estimates above the BAV and detection of esp2 (a marker for the esp gene associated with pathogenic strains of Enterococcus faecium and Enterococcus faecalis), and investigate associations between source contamination levels and land use features. Three BacteriALERT sites on the Chattahoochee River were sampled six times per season in the winter and summer from December 2015 through September 2017, and 11 additional stream sites (synoptic sites) from the CRNRA watershed were sampled once per season. Samples were screened with microbial source tracking (MST) quantitative PCR (qPCR) markers for humans (HF183 Taqman), dogs (DogBact), and ruminants (Rum2Bac), the esp2 qPCR marker, and culturable E. coli. At the BacteriALERT sites, HF183 Taqman concentrations were higher under wet conditions DogBact concentrations were greater in the winter and under wet conditions, and Rum2Bac concentrations were comparatively low throughout the study with no difference across seasons or precipitation conditions. Concentrations of HF183 Taqman, DogBact, and Rum2Bac were positively correlated with culturable E. coli concentrations; however, DogBact had the largest R² value among the three markers, and the forward stepwise regression indicated it was the best predictor of culturable E. coli concentrations at the BacteriALERT sites. Recursive partitioning indicated that BAV exceedances of model-based E. coli estimates were best explained by DogBact concentrations ≥3 gene copies per mL (CN/mL). Detections of esp2 at BacteriALERT sites were best explained by DogBact concentrations ≥11 CN/mL, while detections of esp2 at synoptic sites were best explained by HF183 Taqman ≥29 CN/mL. At the synoptic sites, HF183 Taqman levels were associated with wastewater treatment plant density. However, this relationship was driven primarily by a single site, suggesting possible conveyance issues in that catchment. esp2 detections at synoptic sites were positively associated with development within a 2-km radius and negatively associated with development within the catchment, suggesting multiple sources of esp2 in the watershed. DogBact and Rum2Bac were not associated with the land use features included in our analyses. Implications for Park management include: 1) fecal contamination levels were highest during wet conditions and in the off season when fewer visitors are expected to be participating in water-based recreation, 2) dogs are likely contributors to fecal contamination in the CRNRA and may be sources of pathogenic bacteria indicating further investigation of the origins of this contamination may be warranted as would be research to understand the human health risks from exposure to dog fecal contamination, and 3) high levels of the human marker at one site in the CRNRA watershed suggests more extensive monitoring in that catchment may locate the origin of human fecal contamination detected during this study.

Hydrotransport-Oriented Zn, Cu, and Pb Behavior Assessment and Source Identification in the River Network of a Historically Mined Area in the Hokuroku Basin, Northeast Japan

Aquatic ecosystems continuously receive potentially hazardous heavy metals from natural and anthropogenic sources. Focusing on the origin of heavy metals, this study aims to estimate the load contribution of tributaries from individual watershed and human drainage and to dissect the source of heavy metals, as commonly required for environmental impact assessment. Using integrated water dynamics, Geographic Information System (GIS), and chemical analysis, we identified and evaluated the heavy metal sources of the Kosaka river system in Hokuroku basin, which is a historically mined area in Northeast Japan, both in the high-water and low-water seasons. The migration and diffusion behaviors of heavy metals along with hydro-transport were analyzed, and the effects of mining activities on regional water quality both in the high-water and low-water seasons were clarified. The results indicate that Zn pollution was obvious in the Kosaka River network, especially in the downstream area. The spatial heterogeneity of heavy metal outflows from tributary watersheds was obvious, and the variations had strong correlations with mine site locations. The heavy metal flows in the mainstream increased sharply in the vicinity downstream of the Kosaka refinery drainage outlets. Compared to the low-water season, the influences of human drainage were slighter in high-water season, with lower contribution rates due to the dilution effect of the greater water discharge. Downscale sampling is effective to identify pollutant sources in regional basins.

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.

Dynamics of crAssphage as a human source tracking marker in potentially faecally polluted environments

Recent studies have shown that crAssphage is abundant in human faecal samples worldwide. It has thus been postulated as a potential microbial source tracking (MST) marker to detect human faecal pollution in water. However, an effective implementation of crAssphage in water management strategies will depend on an understanding of its environmental dynamics. In this work, the abundance and temporal distribution of crAssphage was analysed in the effluent of wastewater treatment plants using different sewage treatments, and in two rivers (water and sediments) that differ in pollution impact and flow regime. Additionally, the influence of environmental conditions (temperature and rainfall) on the removal of the marker was studied along a river section, and natural inactivation was assessed by a mesocosms approach. Molecular and culture-based tools were used to compare crAssphage abundance and dynamics with those of bacteria and bacteriophages currently applied as global indicators (E. coli, somatic coliphages, Bacteroides GA17 bacteriophages, and the human-associated MST markers HF183 and HMBif). CrAssphage concentrations in sewage effluent and river samples were similar to those of HF183 and HMBif and higher than other general and/or culture-based indicators (by 2-3 orders of magnitude). Measurement of crAssphage abundance revealed no temporal variability in the effluent, although rainfall events affected the dynamics, possibly through the mobilisation of sediments, where the marker was detected in high concentrations, and an increase in diffuse and point pollution. Another factor affecting crAssphage inactivation was temperature. Its persistence was longer compared with other bacterial markers analysed by qPCR but lower than culturable markers. The results of this study support the use of crAssphage as a human source tracking marker of faecal pollution in water, since it has similar abundances to other molecular human MST markers, yet with a longer persistence in the environment. Nevertheless, its use in combination with infectious bacteriophages is probably advisable.

Linking landscape patterns to sources of water contamination: Implications for tracking fecal contaminants with geospatial and Bayesian approaches

Microbial source tracking (MST) techniques have been designed to identify the host source of fecal contamination in water. However, current MST techniques cannot provide geographic origins of particular sources because they do not provide any spatial information beyond the points of observation. In this study, the associations between landscape patterns and the major sources of microbial contamination were examined and the application of geospatial techniques (e.g., remote sensing and geographic information systems) and Bayesian modeling was explored to track microbial sources over the landscape. The land cover information of three watersheds (the lower Dungeness Watershed, the Middle Rio Grande Watershed, and the Arroyo Burro Watershed) in the United States was obtained either by classifying high resolution satellite images or directly using land cover datasets (e.g., National Land Cover Dataset, 2006 and 2011). Then, the relationship between land use/land cover (LULC) and microbial sources from these three geographically disparate watersheds were analyzed using Bayesian hierarchical models. The results showed the predictive positive associations between human sources of fecal contamination and developed area, between dog sources and grassland, and between bird sources and water, but negative associations between human sources and forest and water areas. Furthermore, the diversity of microbial sources had positive associations with landscape fragmentation and diversity indices. This study demonstrates associations between landscape patterns and major microbial sources and offers new insight in tracking the dominant sources of fecal contamination in water using geospatial and Bayesian techniques.

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds

Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized. Flow composited river samples were collected over low-flow ( n = 89) and rainfall or snowmelt runoff events ( n = 130). Approximately 90% of samples had evidence of human fecal pollution, with highest loads from urban watersheds. Ruminant indicators were found in ∼60-100% of runoff-event samples in agricultural watersheds, with concentrations and loads related to cattle density. Rain depth, season, agricultural tile drainage, and human or cattle density explained variability in daily flux of human or ruminant indicators. Mapping host-associated indicator loads to watershed discharge points sheds light on the type, level, and possible health risk from fecal pollution entering the Great Lakes and can inform total maximum daily load implementation and other management practices to target specific fecal pollution sources.

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

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

Portable platform for rapid in-field identification of human fecal pollution in water

Human fecal contamination of water is a public health risk. However, inadequate testing solutions frustrate timely, actionable monitoring. Bacterial culture-based methods are simple but typically cannot distinguish fecal host source. PCR assays can identify host sources but require expertise and infrastructure. To bridge this gap we have developed a field-ready nucleic acid diagnostic platform and rapid sample preparation methods that enable on-site identification of human fecal contamination within 80 min of sampling. Our platform relies on loop-mediated isothermal amplification (LAMP) of human-associated Bacteroides HF183 genetic markers from crude samples. Oligonucleotide strand exchange (OSD) probes reduce false positives by sequence specifically transducing LAMP amplicons into visible fluorescence that can be photographed by unmodified smartphones. Our assay can detect as few as 17 copies/ml of human-associated HF183 targets in sewage-contaminated water without cross-reaction with canine or feline feces. It performs robustly with a variety of environmental water sources and with raw sewage. We have also developed lyophilized assays and inexpensive 3D-printed devices to minimize cost and facilitate field application.

IMPROVING PREDICTIVE MODELS OF IN-STREAM PHOSPHORUS CONCENTRATION BASED ON NATIONALLY-AVAILABLE SPATIAL DATA COVERAGES

Spatial data are playing an increasingly important role in watershed science and management. Large investments have been made by government agencies to provide nationally-available spatial databases; however, their relevance and suitability for local watershed applications is largely unscrutinized. We investigated how goodness of fit and predictive accuracy of total phosphorus (TP) concentration models developed from nationally-available spatial data could be improved by including local watershed-specific data in the East Fork of the Little Miami River, Ohio, a 1290 km² watershed. We also determined whether a spatial stream network (SSN) modeling approach improved on multiple linear regression (nonspatial) models. Goodness of fit and predictive accuracy were highest for the SSN model that included local covariates, and lowest for the nonspatial model developed from national data. Septic systems and point source TP loads were significant covariates in the local models. These local data not only improved the models but enabled a more explicit interpretation of the processes affecting TP concentrations than more generic national covariates. The results suggest that SSN modeling greatly improves prediction and should be applied when using national covariates. Including local covariates further increases the accuracy of TP predictions throughout the studied watershed; such variables should be included in future national databases, particularly the locations of septic systems.

Isolating the impact of septic systems on fecal pollution in streams of suburban watersheds in Georgia, United States

The presence of multiple sources of fecal pollution at the watershed level presents challenges to efforts aimed at identifying the influence of septic systems. In this study multiple approaches including targeted sampling and monitoring of host-specific Bacteroidales markers were used to identify the impact of septic systems on microbial water quality. Twenty four watersheds with septic density ranging from 8 to 373 septic units/km² were monitored for water quality under baseflow conditions over a 3-year period. The levels of the human-associated HF183 marker, as well as total and ruminant Bacteroidales, were quantified using quantitative polymerase chain reaction. Human-associated Bacteroidales yield was significantly higher in high density watersheds compared to low density areas and was negatively correlated (r = -0.64) with the average distance of septic systems to streams in the spring season. The human marker was also positively correlated with the total Bacteroidales marker, suggesting that the human source input was a significant contributor to total fecal pollution in the study area. Multivariable regression analysis indicates that septic systems, along with forest cover, impervious area and specific conductance could explain up to 74% of the variation in human fecal pollution in the spring season. The results suggest septic system impact through contributions to groundwater recharge during baseflow or failing septic system input, especially in areas with >87 septic units/km². This study supports the use of microbial source tracking approaches along with traditional fecal indicator bacteria monitoring and land use characterization in a tiered approach to isolate the influence of septic systems on water quality in mixed-use watersheds.

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

There is growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality management. The transition from a research tool to a standardized protocol requires a high degree of confidence in data quality across laboratories. Data quality is typically determined through a series of specifications that ensure good experimental practice and the absence of bias in the results due to DNA isolation and amplification interferences. However, there is currently a lack of consensus on how best to evaluate and interpret human fecal source identification qPCR experiments. This is, in part, due to the lack of standardized protocols and information on interlaboratory variability under conditions for data acceptance. The aim of this study is to provide users and reviewers with a complete series of conditions for data acceptance derived from a multiple laboratory data set using standardized procedures. To establish these benchmarks, data from HF183/BacR287 and HumM2 human-associated qPCR methods were generated across 14 laboratories. Each laboratory followed a standardized protocol utilizing the same lot of reference DNA materials, DNA isolation kits, amplification reagents, and test samples to generate comparable data. After removal of outliers, a nested analysis of variance (ANOVA) was used to establish proficiency metrics that include lab-to-lab, replicate testing within a lab, and random error for amplification inhibition and sample processing controls. Other data acceptance measurements included extraneous DNA contamination assessments (no-template and extraction blank controls) and calibration model performance (correlation coefficient, amplification efficiency, and lower limit of quantification). To demonstrate the implementation of the proposed standardized protocols and data acceptance criteria, comparable data from two additional laboratories were reviewed. The data acceptance criteria proposed in this study should help scientists, managers, reviewers, and the public evaluate the technical quality of future findings against an established benchmark.

Widespread detection of human- and ruminant-origin Bacteroidales markers in subtidal waters of the Salish Sea in Washington State

Rising populations around coastal systems are increasing the threats to marine water quality. To assess anthropogenic fecal influence, subtidal waters were examined monthly for human- and ruminant-sourced Bacteroidales markers at 80 sites across six oceanographic basins of the Salish Sea (Washington State) from April through October, 2011. In the basins containing cities with individual populations>190,000, >50% of sites were positive for the human marker, while in the basins with high densities of dairy and cattle operations, ∼30% of sites were positive for the ruminant marker. Marker prevalence was elevated in spring (April and May) and fall (October) and reduced during summer (June through September), corresponding with seasonal precipitation. By logistic regression, the odds of human marker detection increased with percentage of adjacent catchment impervious surface, dissolved nitrate concentration, and abundance of low nucleic acid bacteria, but decreased with salinity and chlorophyll fluorescence. The odds of ruminant marker detection increased with dissolved ammonium concentration, mean flow rate for the nearest river, and adjacent shoreline length. These relationships are consistent with terrestrial to marine water flow as a transport mechanism. Thus, Bacteroidales markers traditionally used for identifying nearby sources can be used for assessing anthropogenic fecal inputs to regional marine ecosystems.

Linking fecal bacteria in rivers to landscape, geochemical, and hydrologic factors and sources at the basin scale

Linking fecal indicator bacteria concentrations in large mixed-use watersheds back to diffuse human sources, such as septic systems, has met limited success. In this study, 64 rivers that drain 84% of Michigan's Lower Peninsula were sampled under baseflow conditions for Escherichia coli, Bacteroides thetaiotaomicron (a human source-tracking marker), landscape characteristics, and geochemical and hydrologic variables. E. coli and B. thetaiotaomicron were routinely detected in sampled rivers and an E. coli reference level was defined (1.4 log10 most probable number⋅100 mL(-1)). Using classification and regression tree analysis and demographic estimates of wastewater treatments per watershed, septic systems seem to be the primary driver of fecal bacteria levels. In particular, watersheds with more than 1,621 septic systems exhibited significantly higher concentrations of B. thetaiotaomicron. This information is vital for evaluating water quality and health implications, determining the impacts of septic systems on watersheds, and improving management decisions for locating, constructing, and maintaining on-site wastewater treatment systems.

Microbial Source Tracking in Adjacent Karst Springs

Modern man-made environments, including urban, agricultural, and industrial environments, have complex ecological interactions among themselves and with the natural surroundings. Microbial source tracking (MST) offers advanced tools to resolve the host source of fecal contamination beyond indicator monitoring. This study was intended to assess karst spring susceptibilities to different fecal sources using MST quantitative PCR (qPCR) assays targeting human, bovine, and swine markers. It involved a dual-time monitoring frame: (i) monthly throughout the calendar year and (ii) daily during a rainfall event. Data integration was taken from both monthly and daily MST profile monitoring and improved identification of spring susceptibility to host fecal contamination; three springs located in close geographic proximity revealed different MST profiles. The Giach spring showed moderate fluctuations of MST marker quantities amid wet and dry samplings, while the Zuf spring had the highest rise of the GenBac3 marker during the wet event, which was mirrored in other markers as well. The revelation of human fecal contamination during the dry season not connected to incidents of raining leachates suggests a continuous and direct exposure to septic systems. Pigpens were identified in the watersheds of Zuf, Shefa, and Giach springs and on the border of the Gaaton spring watershed. Their impact was correlated with partial detection of the Pig-2-Bac marker in Gaaton spring, which was lower than detection levels in all three of the other springs. Ruminant and swine markers were detected intermittently, and their contamination potential during the wet samplings was exposed. These results emphasized the importance of sampling design to utilize the MST approach to delineate subtleties of fecal contamination in the environment.

Incorporating expert judgments in utility evaluation of bacteroidales qPCR assays for microbial source tracking in a drinking water source

Several assays for the detection of host-specific genetic markers of the order Bacteroidales have been developed and used for microbial source tracking (MST) in environmental waters. It is recognized that the source-sensitivity and source-specificity are unknown and variable when introducing these assays in new geographic regions, which reduces their reliability and use. A Bayesian approach was developed to incorporate expert judgments with regional assay sensitivity and specificity assessments in a utility evaluation of a human and a ruminant-specific qPCR assay for MST in a drinking water source. Water samples from Lake Rådasjön were analyzed for E. coli, intestinal enterococci and somatic coliphages through cultivation and for human (BacH) and ruminant-specific (BacR) markers through qPCR assays. Expert judgments were collected regarding the probability of human and ruminant fecal contamination based on fecal indicator organism data and subjective information. Using Bayes formula, the conditional probability of a true human or ruminant fecal contamination given the presence of BacH or BacR was determined stochastically from expert judgments and regional qPCR assay performance, using Beta distributions to represent uncertainties. A web-based computational tool was developed for the procedure, which provides a measure of confidence to findings of host-specific markers and demonstrates the information value from these assays.

An environmental survey of surface waters using mitochondrial DNA from human, bovine and porcine origin as fecal source tracking markers

Fecal contamination of surface waters is one the major sources of waterborne pathogens and consequently, is an important concern for public health. For reliable fecal source tracking (FST) monitoring, there is a need for a multi-marker toolbox as no single all-encompassing method currently exists. Mitochondrial DNA (mtDNA) as a source tracking marker has emerged as a promising animal-specific marker. However, very few comprehensive field studies were done on the occurrence of this marker in surface waters. In this report, water samples were obtained from 82 sites in different watersheds over a six year period. The samples were analyzed for the presence of human, bovine and porcine mtDNA by endpoint nested PCR, along with the human-specific Bacteroidales HF183 marker. These sites represented a mix of areas with different anthropogenic activities, natural, urban and agricultural. The occurrences of mitoHu (human), mitoBo (bovine), mitoPo (porcine) and HF183 specific PCR amplifications from the samples were 46%, 23%, 6% and 50%, respectively. The occurrence of mitoHu and HF183 was high in all environment types with higher occurrence in the natural and urban areas, whereas the occurrence of mitoBo was higher in agricultural areas. FST marker concentrations were measured by real-time PCR for samples positive for these markers. The concentration of the mitoHu markers was one order of magnitude lower than HF183. There was co-linearity between the concentrations of the mitoHu and HF183 markers. Co-linearity was also observed between HF183 concentration and fecal coliform levels. Such a relationship was not observed between the mitoHu concentration and fecal coliform levels. In summary, our results showed a high incidence of human fecal pollution throughout the environment while demonstrating the potential of mtDNA as suitable FST markers.

Integrating bacterial and viral water quality assessment to predict swimming-associated illness at a freshwater beach: a cohort study

BACKGROUND & OBJECTIVE

Recreational waters impacted by fecal contamination have been linked to gastrointestinal illness in swimmer populations. To date, few epidemiologic studies examine the risk for swimming-related illnesses based upon simultaneous exposure to more than one microbial surrogate (e.g. culturable E. coli densities, genetic markers). We addressed this research gap by investigating the association between swimming-related illness frequency and water quality determined from multiple bacterial and viral genetic markers.

METHODS

Viral and bacterial genetic marker densities were determined from beach water samples collected over 23 weekend days and were quantified using quantitative polymerase chain reaction (qPCR). These genetic marker data were paired with previously determined human exposure data gathered as part of a cohort study carried out among beach users at East Fork Lake in Ohio, USA in 2009. Using previously unavailable genetic marker data in logistic regression models, single- and multi-marker/multi-water quality indicator approaches for predicting swimming-related illness were evaluated for associations with swimming-associated gastrointestinal illness.

RESULTS

Data pertaining to genetic marker exposure and 8- or 9-day health outcomes were available for a total of 600 healthy susceptible swimmers, and with this population we observed a significant positive association between human adenovirus (HAdV) exposure and diarrhea (odds ratio  = 1.6; 95% confidence interval: 1.1-2.3) as well as gastrointestinal illness (OR  = 1.5; 95% CI: 1.0-2.2) upon adjusting for culturable E. coli densities in multivariable models. No significant associations between bacterial genetic markers and swimming-associated illness were observed.

CONCLUSIONS

This study provides evidence that a combined measure of recreational water quality that simultaneously considers both bacterial and viral densities, particularly HAdV, may improve prediction of disease risk than a measure of a single agent in a beach environment likely influenced by nonpoint source human fecal contamination.

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

Urban runoff can carry a variety of pollutants into recreational beaches, often including bacterial pathogens and indicators of fecal contamination. To develop complete recreational criteria and risk assessments, it is necessary to understand conditions under which human contamination could be present at beaches solely impacted by urban runoff. Accurately estimating risk requires understanding sources, concentrations, and transport mechanisms of microbial contaminants in these environments. By applying microbial source tracking methods and empirical modeling, we assessed the presence and level of human contamination at urban runoff impacted recreational beaches. We also identified environmental parameters and pollution sources that can influence the concentration and transport of culturable and molecular fecal indicator bacteria (FIB) in systems impacted solely by urban runoff. Water samples and physico-chemical parameters were collected from shoreline locations from three South Carolina (SC) beaches (five locations per beach) and two Florida (FL) beaches (three locations per beach). Each SC beach was directly impacted by swashes or tidal creeks receiving stormwater runoff from the urbanized area and therefore were designated as swash drain associated (SDA) beaches, while FL beaches were designated as non-swash drain associated (NSDA). Sampling in swash drains (SD; three sites per SD) directly impacting each SC beach was also conducted. Results indicate that although culturable (enterococci) and real-time quantitative polymerase chain reaction (qPCR) (EC23S857, Entero1, and GenBac3) FIB concentrations were, on average, higher at SD locations, SDA beaches did not have consistently higher molecular FIB signals compared to NSDA beaches. Both human-associated markers (HF183 and HumM2) were concomitantly found only at SDA beaches. Bacteroidales species-specific qPCR markers (BsteriF1 and BuniF2) identified differences in the Bacteroidales community, depending on beach type. The marker for general Bacteroidales was most abundant at SD locations and exhibited a high correlation with both culturable and other molecular markers. Combining molecular information with predictive modeling allowed us to identify both alongshore movement of currents and SD outflow as significant influences on the concentration of molecular and culturable indicators in the bathing zone. Data also suggests that combining methodologies is a useful and cost effective approach to help understand transport dynamics of fecal contamination and identify potential sources of contamination at marine beaches.

Baseline and storm event monitoring of Bacteroidales marker concentrations and enteric pathogen presence in a rural Canadian watershed

Bacteroidales 16S rRNA gene markers were evaluated for their use as a microbial source tracking tool in a well characterized 750 ha agricultural watershed in Nova Scotia, Canada. Water quality monitoring was conducted following the validation of host-specific and universal Bacteroidales (AllBac) markers for their proficiency in this particular geographic region, which provided further evidence that these markers are geographically stable. Increasing Escherichia coli concentrations were positively correlated (p < 0.01) with concentrations of the AllBac marker in water samples, suggesting that this universal marker is more suited as a positive DNA control rather than as an indicator of recent fecal contamination. Ruminant (BacR) and bovine (CowM2) specific marker detection was associated with increased runoff due to precipitation in sub-watersheds putatively impacted by cattle farming, demonstrating that the BacR and CowM2 markers can be used to detect the recent introduction of fecal matter from cattle farming activities during rainfall events. However, the human associated marker (BacH) was only detected once in spite of numerous on-site residential wastewater treatment systems in the watershed, suggesting that this assay is not sensitive enough to detect this type of human sewage source. E. coli O157:H7 and Salmonella spp. DNA was not detected in any of the 149 watershed samples; however, 114 (76.5%) of those samples tested positive for Campylobacter spp. No significant correlation (p > 0.05) was found between Campylobacter spp. presence and either E. coli or AllBac marker levels. Further studies should be conducted to assess the origins of Campylobacter spp. in these types of watersheds, and to quantify pathogen cell numbers to allow for a human health risk assessment.

Characterization of sources and loadings of fecal pollutants using microbial source tracking assays in urban and rural areas of the Grand River Watershed, Southwestern Ontario

Sources of fecal water pollution were assessed in the Grand River and two of its tributaries (Ontario, Canada) using total and host-specific (human and bovine) Bacteroidales genetic markers in conjunction with reference information, such as land use and weather. In-stream levels of the markers and culturable Escherichia coli were also monitored during multiple rain events to gain information on fecal loadings to catchment from diffuse sources. Elevated human-specific marker levels were accurately identified in river water impacted by a municipal wastewater treatment plant (WWTP) effluent and at a downstream site in the Grand River. In contrast, the bovine-specific marker showed high levels of cattle fecal pollution in two tributaries, both of which are characterized as intensely farmed areas. The bovine-specific Bacteroidales marker increased with rainfall in the agricultural tributaries, indicating enhanced loading of cattle-derived fecal pollutants to river from non-point sources following rain events. However, rain-triggered fecal loading was not substantiated in urban settings, indicating continuous inputs of human-originated fecal pollutants from point sources, such as WWTP effluent. This study demonstrated that the Bacteroidales source tracking assays, in combination with land use information and hydrological data, may provide additional insight into the spatial and temporal distribution of source-specific fecal contamination in streams impacted by varying land uses. Using the approach described in this study may help to characterize impacted water sources and to design targeted land use management plans in other watersheds in the future.

Improved HF183 quantitative real-time PCR assay for characterization of human fecal pollution in ambient surface water samples

Quantitative real-time PCR (qPCR) assays that target the human-associated HF183 bacterial cluster within members of the genus Bacteroides are among the most widely used methods for the characterization of human fecal pollution in ambient surface waters. In this study, we show that a current TaqMan HF183 qPCR assay (HF183/BFDrev) routinely forms nonspecific amplification products and introduce a modified TaqMan assay (HF183/BacR287) that alleviates this problem. The performance of each qPCR assay was compared in head-to-head experiments investigating limits of detection, analytical precision, predicted hybridization to 16S rRNA gene sequences from a reference database, and relative marker concentrations in fecal and sewage samples. The performance of the modified HF183/BacR287 assay is equal to or improves upon that of the original HF183/BFDrev assay. In addition, a qPCR chemistry designed to combat amplification inhibition and a multiplexed internal amplification control are included. In light of the expanding use of PCR-based methods that rely on the detection of extremely low concentrations of DNA template, such as qPCR and digital PCR, the new TaqMan HF183/BacR287 assay should provide more accurate estimations of human-derived fecal contaminants in ambient surface waters.

Coherence among different microbial source tracking markers in a small agricultural stream with or without livestock exclusion practices

Over 1,400 water samples were collected biweekly over 6 years from an intermittent stream protected and unprotected from pasturing cattle. The samples were monitored for host-specific Bacteroidales markers, Cryptosporidium species/genotypes, viruses and coliphages associated with humans or animals, and bacterial zoonotic pathogens. Ruminant Bacteroidales markers did not increase within the restricted cattle access reach of the stream, whereas the ruminant Bacteroidales marker increased significantly in the unrestricted cattle access reach. Human Bacteroidales markers significantly increased downstream of homes where septic issues were documented. Wildlife Bacteroidales markers were detected downstream of the cattle exclusion practice where stream and riparian habitat was protected, but detections decreased after the unrestricted pasture, where the stream and riparian zone was unprotected from livestock. Detection of a large number of human viruses was shown to increase downstream of homes, and similar trends were observed for the human Bacteroidales marker. There was considerable interplay among biomarkers with stream flow, season, and the cattle exclusion practices. There were no to very weak associations with Bacteroidales markers and bacterial, viral, and parasitic pathogens. Overall, discrete sample-by-sample coherence among the different microbial source tracking markers that expressed a similar microbial source was minimal, but spatial trends were physically meaningful in terms of land use (e.g., beneficial management practice) effects on sources of fecal pollution.

Determining hot spots of fecal contamination in a tropical watershed by combining land-use information and meteorological data with source-specific assays

The objective of this study was to combine knowledge of environmental, topographical, meteorological, and anthropologic factors in the Río Grande de Arecibo (RGA) watershed in Puerto Rico with information provided by microbial source tracking (MST) to map hot spots (i.e., likely sources) of fecal contamination. Water samples were tested for the presence of human and bovine fecal contamination in addition to fecal indicator bacteria and correlated against several land uses and the density of septic tanks, sewers, and latrines. Specifically, human sources were positively correlated with developed (r = 0.68), barren land uses (r = 0.84), density of septic tanks (r = 0.78), slope (r = 0.63), and the proximity to wastewater treatment plants (WWTPs) (r = 0.82). Agricultural land, the number of upstream National Pollution Discharge Elimination System (NPDES) facilities, and density of latrines were positively associated with the bovine marker (r = 0.71; r = 0.74; and r = 0.68, respectively). Using this information, we provided a hot spot map, which shows areas that should be closely monitored for fecal contamination in the RGA watershed. The results indicated that additional bovine assays are needed in tropical regions. We concluded that meteorological, topographical, anthropogenic, and land cover data are needed to evaluate and verify the performance of MST assays and, therefore, to identify important sources of fecal contamination in environmental waters.

Impact of mixed land-use practices on the microbial water quality in a subtropical coastal watershed

Surface runoff water is an important non-point source of fecal pollution to downstream water; however, there is a lack of systematic studies on the microbial quality of surface runoff water from watersheds with mixed land uses. In this study water samples from 12 surface runoff holding water bodies (SRW), which collected runoff from various patterns of land use within the St. Lucie watershed along the southeastern coastline of Florida, were collected monthly for 22 months. The concentration of fecal indicator bacteria (FIB) and frequency of detection of Salmonella and host specific markers (HF183, CF128, CF193, and HS-esp) were determined, and their associations with land use, rainfall, and water physico-chemical parameters were investigated. Higher FIB concentrations were observed from urban land and cattle ranch sites. Within the same primary land use pattern, different sub-patterns did not have the same level of FIB: golf communities contributed less to fecal pollution than residential areas, and plant nursery sites contained relative higher FIB concentrations than other agricultural sites. Salmonella, CF128, and CF193 markers were more frequently detected from the cattle ranch sites. In contrast the frequency of detecting human specific markers (HF183 and HS-esp) was much higher in residential sites. Rainfall positively affected the concentration of FIB and occurrence of Salmonella, possibly by providing more inputs or mobilizing the sources from sediments. Water temperature, dissolved organic carbon (DOC), and nutrient levels were positively correlated with FIB concentrations and occurrence in SRW, possibly by promoting their growth and survival. This study indicated the need for site specific mitigation strategies to improve SRW and downstream water quality.

Sensitive detection of sample interference in environmental qPCR

Sample interference in environmental applications of quantitative PCR (qPCR) can prevent accurate estimations of molecular markers in the environment. We developed a spike-and-recovery approach using a mutant strain of Escherichia coli that contains a chromosomal insertion of a mutant GFP gene. The method was tested in water samples by separately reducing extraction efficiency or adding humic acids and ethanol, compounds that often contaminate environmental DNA extracts, and analyzing qPCR amplification of the spiked E. coli control and human fecal Bacteroides markers (HF183 and HF134). This approach, coupled with previously developed kinetic outlier detection (KOD) methods, allowed sensitive detection of PCR inhibition at much lower inhibitor concentrations than alternative approaches using Cq values or amplification efficiencies. Although HF183 was more sensitive to the effects of qPCR inhibitors than the E. coli control assay, KOD methods correctly identified inhibition of both control and HF183 assays in samples containing as little as 0.1 ng humic acids per reaction or 5% ethanol. Because sigmoidal modeling methods allow distinction of qPCR inhibition from poor DNA recovery, we were able to simultaneously identify qPCR-inhibited reactions and estimate recovery of nucleic acids in environmental samples using a single control assay. Since qPCR is currently used to estimate important water quality parameters that have serious economic and human health outcomes, these results are timely. While we demonstrate the methods in the context of water quality regulation, they will be useful in all areas of environmental research that use qPCR.