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The impacts of nucleic acid-based methods - such as PCR and sequencing - to detect and analyze indicators, genetic markers or molecular signatures of microbial faecal pollution in health-related water quality research were assessed by rigorous literature analysis. A wide range of application areas and study designs has been identified since the first application more than 30 years ago (>1100 publications). Given the consistency of methods and assessment types, we suggest defining this emerging part of science as a new discipline: genetic faecal pollution diagnostics (GFPD) in health-related microbial water quality analysis. Undoubtedly, GFPD has already revolutionized faecal pollution detection (i.e., traditional or alternative general faecal indicator/marker analysis) and microbial source tracking (i.e., host-associated faecal indicator/marker analysis), the current core applications. GFPD is also expanding to many other research areas, including infection and health risk assessment, evaluation of microbial water treatment, and support of wastewater surveillance. In addition, storage of DNA extracts allows for biobanking, which opens up new perspectives. The tools of GFPD can be combined with cultivation-based standardized faecal indicator enumeration, pathogen detection, and various environmental data types, in an integrated data analysis approach. This comprehensive meta-analysis provides the scientific status quo of this field, including trend analyses and literature statistics, outlining identified application areas, and discusses the benefits and challenges of nucleic acid-based analysis in GFPD., (© The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

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 log 10 host-associated genetic marker fecal score ratios were estimated to compare pollutant source inferences based on variable routine water quality monitoring practices. Eligible log 10 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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier Ltd.)

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., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The authors have no financial stake in the products described or in this research. The employer of two of the authors (AS and SD), the University of Illinois at Chicago, is contracted by the Chicago Park District to conduct beach monitoring, and that monitoring is managed by those authors. The beaches managed by the Chicago Park District are the subject of the manuscript., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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., Competing Interests: The authors have declared that no competing interests exist.

Numerous bacterial genetic markers are available for the molecular detection of human sources of fecal pollution in environmental waters. However, widespread application is hindered by a lack of knowledge regarding geographical stability, limiting implementation to a small number of well-characterized regions. This study investigates the geographic distribution of five human-associated genetic markers (HF183/BFDrev, HF183/BacR287, BacHum-UCD, BacH, and Lachno2) in municipal wastewaters (raw and treated) from 29 urban and rural wastewater treatment plants (750-4 400 000 population equivalents) from 13 countries spanning six continents. In addition, genetic markers were tested against 280 human and nonhuman fecal samples from domesticated, agricultural and wild animal sources. Findings revealed that all genetic markers are present in consistently high concentrations in raw (median log 10 7.2-8.0 marker equivalents (ME) 100 mL -1 ) and biologically treated wastewater samples (median log 10 4.6-6.0 ME 100 mL -1 ) regardless of location and population. The false positive rates of the various markers in nonhuman fecal samples ranged from 5% to 47%. Results suggest that several genetic markers have considerable potential for measuring human-associated contamination in polluted environmental waters. This will be helpful in water quality monitoring, pollution modeling and health risk assessment (as demonstrated by QMRAcatch) to guide target-oriented water safety management across the globe.

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.

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., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Waterborne diseases represent a significant public health risk worldwide and can originate from contact with water contaminated with human fecal material. We describe a real-time quantitative PCR (qPCR) method that targets a genetic marker of the human-associated Bacteroides dorei for identification of human fecal pollution in ambient water samples. The following protocol includes water sample collection, filtration, DNA isolation with a sample processing control, qPCR amplification with an internal amplification control, and quality control data analysis.

The contribution of fecal pollution from dogs in urbanized areas can be significant and is an often underestimated problem. Microbial source tracking methods (MST) utilizing quantitative PCR of dog-associated gene sequences encoding 16S rRNA of Bacteroidales are a useful tool to estimate these contributions. However, data about the performance of available assays are scarce. The results of a multi-laboratory study testing two assays for the determination of dog-associated Bacteroidales (DogBact and BacCan-UCD) on 64 single and mixed fecal source samples created from pooled fecal samples collected in California are presented here. Standardization of qPCR data treatment lowered inter-laboratory variability of sensitivity and specificity results. Both assays exhibited 100% sensitivity. Normalization methods are presented that eliminated random and confirmed non-target responses. The combination of standardized qPCR data treatment, use of normalization via a non-target specific Bacteroidales assay (GenBac3), and application of threshold criteria improved the calculated specificity significantly for both assays. Such measures would reasonably improve MST data interpretation not only for canine-associated assays, but for all qPCR assays used in identifying and monitoring fecal pollution in the environment., (Copyright © 2013. Published by Elsevier Ltd.)

The last decade has seen development of numerous new microbial source tracking (MST) methodologies, but many of these have been tested in just a few laboratories with a limited number of fecal samples. This method evaluation study examined the specificity and sensitivity of 41 MST methodologies by analyzing data generated in 27 laboratories. MST methodologies that targeted human, cow, ruminant, dog, gull, pig, horse, and sheep were tested against sewage, septage, human, cow, dog, deer, pig, chicken, pigeon, gull, horse, and goose fecal samples. Each laboratory received 64 blind samples containing a single source (singletons) or two sources (doubletons), as well as diluted singleton samples to assess method sensitivity. Laboratories utilized their own protocols when performing the methods and data were deposited in a central database before samples were unblinded. Between one and seven laboratories tested each method. The most sensitive and specific assays, based on an analysis of presence/absence of each marker in target and non-target fecal samples, were HF183 endpoint and HF183SYBR (human), CF193 and Rum2Bac (ruminant), CowM2 and CowM3 (cow), BacCan (dog), Gull2SYBR and LeeSeaGull (gull), PF163 and pigmtDNA (pig), HoF597 (horse), PhyloChip (pig, horse, chicken, deer), Universal 16S TRFLP (deer), and Bacteroidales 16S TRFLP (pig, horse, chicken, deer); all had sensitivity and specificity higher than 80% in all or the majority of laboratories. When the abundance of MST markers in target and non-target fecal samples was examined, some assays that performed well in the binary analysis were found to not be sensitive enough as median concentrations fell below a minimum abundance criterion (set at 50 copies per colony forming units of enterococci) in target fecal samples. Similarly, some assays that cross-reacted with non-target fecal sources in the binary analysis were found to perform well in a quantitative analysis because the cross-reaction occurred at very low levels. Based on a quantitative analysis, the best performing methods were HF183Taqman and BacH (human), Rum2Bac and BacR (ruminant), LeeSeaGull (gull), and Pig2Bac (pig); no cow or dog-specific assay met the quantitative specificity and sensitivity criteria. Some of the best performing assays in the study were run by just one laboratory so further testing of assay portability is needed. While this study evaluated the marker performance in defined samples, further field testing as well as development of frameworks for fecal source allocation and risk assessment are needed., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Fecal pollution is measured in surface waters using culture-based measurements of enterococci and Escherichia coli bacteria. Source apportionment of these two fecal indicator bacteria is an urgent need for prioritizing remediation efforts and quantifying health risks associated with source-specific pathogens. There are a number of quantitative real-time PCR (QPCR) assays that estimate concentrations of source-associated genetic markers; however, their concentrations are not necessarily amenable to source apportionment because the markers may differ in prevalence across sources. Here we mathematically derive and test, under ideal conditions, a method that utilizes the ratios of fecal source-associated genetic markers and culture and molecular measurements of general fecal indicators to apportion enterococci and E. coli. The source contribution is approximately equal to the ratio of the source-associated and the general fecal indicator concentrations in a water sample divided by their ratio in the source material, so long as cross-reactivity is negligible. We illustrate the utility of the ratio method using samples consisting of mixtures of various fecal pollution sources. The results from the ratio method correlated well with the actual source apportionment in artificial samples. However, aging of contamination can confound source allocation predictions. In particular, culturable enterococci and E. coli, the organisms presently regulated in the United States and much of the world, decay at different rates compared to source-associated markers and as a result cannot be apportioned using this method. However, limited data suggest a similar decay rate between source-associated and QPCR-measured Enterococcus and E. coli genetic markers, indicating that apportionment may be possible for these organisms; however further work is needed to confirm., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The characteristics of fecal sources, and the ways in which they are measured, can profoundly influence the interpretation of which sources are contaminating a body of water. Although feces from various hosts are known to differ in mass and composition, it is not well understood how those differences compare across fecal sources and how differences depend on characterization methods. This study investigated how nine different fecal characterization methods provide different measures of fecal concentration in water, and how results varied across twelve different fecal pollution sources. Sources investigated included chicken, cow, deer, dog, goose, gull, horse, human, pig, pigeon, septage and sewage. A composite fecal slurry was prepared for each source by mixing feces from 6 to 22 individual samples with artificial freshwater. Fecal concentrations were estimated by physical (wet fecal mass added and total DNA mass extracted), culture-based (Escherichia coli and enterococci by membrane filtration and defined substrate), and quantitative real-time PCR (Bacteroidales, E. coli, and enterococci) characterization methods. The characteristics of each composite fecal slurry and the relationships between physical, culture-based and qPCR-based characteristics varied within and among different fecal sources. An in silico exercise was performed to assess how different characterization methods can impact identification of the dominant fecal pollution source in a mixed source sample. A comparison of simulated 10:90 mixtures based on enterococci by defined substrate predicted a source reversal in 27% of all possible combinations, while mixtures based on E. coli membrane filtration resulted in a reversal 29% of the time. This potential for disagreement in minor or dominant source identification based on different methods of measurement represents an important challenge for water quality managers and researchers., (Published by Elsevier Ltd.)

Microbial source tracking (MST) methods were evaluated in the Source Identification Protocol Project (SIPP), in which 27 laboratories compared methods to identify host sources of fecal pollution from blinded water samples containing either one or two different fecal types collected from California. This paper details lessons learned from the SIPP study and makes recommendations to further advance the field of MST. Overall, results from the SIPP study demonstrated that methods are available that can correctly identify whether particular host sources including humans, cows and birds have contributed to contamination in a body of water. However, differences between laboratory protocols and data processing affected results and complicated interpretation of MST method performance in some cases. This was an issue particularly for samples that tested positive (non-zero Ct values) but below the limits of quantification or detection of a PCR assay. Although false positives were observed, such samples in the SIPP study often contained the fecal pollution source that was being targeted, i.e., the samples were true positives. Given these results, and the fact that MST often requires detection of targets present in low concentrations, we propose that such samples be reported and identified in a unique category to facilitate data analysis and method comparisons. Important data can be lost when such samples are simply reported as positive or negative. Actionable thresholds were not derived in the SIPP study due to limitations that included geographic scope, age of samples, and difficulties interpreting low concentrations of target in environmental samples. Nevertheless, the results of the study support the use of MST for water management, especially to prioritize impaired waters in need of remediation. Future integration of MST data into quantitative microbial risk assessments and other models could allow managers to more efficiently protect public health based on site conditions., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The State of California has mandated the preparation of a guidance document on the application of fecal source identification methods for recreational water quality management. California contains the fifth highest population of cattle in the United States, making the inclusion of cow-associated methods a logical choice. Because the performance of these methods has been shown to change based on geography and/or local animal feeding practices, laboratory comparisons are needed to determine which assays are best suited for implementation. We describe the performance characterization of two end-point PCR assays (CF128 and CF193) and five real-time quantitative PCR (qPCR) assays (Rum2Bac, BacR, BacCow, CowM2, and CowM3) reported to be associated with either ruminant or cattle feces. Each assay was tested against a blinded set of 38 reference challenge filters (19 duplicate samples) containing fecal pollution from 12 different sources suspected to impact water quality. The abundance of each host-associated genetic marker was measured for qPCR-based assays in both target and non-target animals and compared to quantities of total DNA mass, wet mass of fecal material, as well as Bacteroidales, and enterococci determined by 16S rRNA qPCR and culture-based approaches (enterococci only). Ruminant- and cow-associated genetic markers were detected in all filters containing a cattle fecal source. However, some assays cross-reacted with non-target pollution sources. A large amount of variability was evident across laboratories when protocols were not fixed suggesting that protocol standardization will be necessary for widespread implementation. Finally, performance metrics indicate that the cattle-associated CowM2 qPCR method combined with either the BacR or Rum2Bac ruminant-associated methods are most suitable for implementation., (Published by Elsevier Ltd.)

Many PCR-based methods for microbial source tracking (MST) have been developed and validated within individual research laboratories. Inter-laboratory validation of these methods, however, has been minimal, and the effects of protocol standardization regimes have not been thoroughly evaluated. Knowledge of factors influencing PCR in different laboratories is vital to future technology transfer for use of MST methods as a tool for water quality management. In this study, a blinded set of 64 filters (containing 32 duplicate samples generated from 12 composite fecal sources) were analyzed by three to five core laboratories with a suite of PCR-based methods utilizing standardized reagents and protocols. Repeatability (intra-laboratory variability) and reproducibility (inter-laboratory variability) of observed results were assessed. When standardized methodologies were used, intra- and inter-laboratory %CVs were generally low (median %CV 0.1-3.3% and 1.9-7.1%, respectively) and comparable to those observed in similar inter-laboratory validation studies performed on other methods of quantifying fecal indicator bacteria (FIB) in environmental samples. ANOVA of %CV values found three human-associated methods (BsteriF1, BacHum, and HF183Taqman) to be similarly reproducible (p > 0.05) and significantly more reproducible (p < 0.05) than HumM2. This was attributed to the increased variability associated with low target concentrations detected by HumM2 (approximately 1-2 log10copies/filter lower) compared to other human-associated methods. Cow-associated methods (BacCow and CowM2) were similarly reproducible (p > 0.05). When using standardized protocols, variance component analysis indicated sample type (fecal source and concentration) to be the major contributor to total variability with that from replicate filters and inter-laboratory analysis to be within the same order of magnitude but larger than inherent intra-laboratory variability. However, when reagents and protocols were not standardized, inter-laboratory %CV generally increased with a corresponding decline in reproducibility. Overall, these findings verify the repeatability and reproducibility of these MST methods and highlight the need for standardization of protocols and consumables prior to implementation of larger scale MST studies involving multiple laboratories., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described bovine feces-specific genetic markers and a method for the enumeration of these markers using a Markov chain Monte Carlo approach. Both assays exhibited a range of quantification from 25 to 2 x 10(6) copies of target DNA, with a coefficient of variation of <2.1%. One of these assays can be multiplexed with an internal amplification control to simultaneously detect the bovine-specific genetic target and presence of amplification inhibitors. The assays detected only cattle fecal specimens when tested against 204 fecal DNA extracts from 16 different animal species and also demonstrated a broad distribution among individual bovine samples (98 to 100%) collected from five geographically distinct locations. The abundance of each bovine-specific genetic marker was measured in 48 individual samples and compared to quantitative PCR-enumerated quantities of rRNA gene sequences representing total Bacteroidetes, Bacteroides thetaiotaomicron, and enterococci in the same specimens. Acceptable assay performance combined with the prevalence of DNA targets across different cattle populations provides experimental evidence that these quantitative assays will be useful in monitoring bovine fecal pollution in ambient waters.

The objectives of this study were to elucidate spatial and temporal dynamics in source-specific Bacteroidales 16S rRNA genetic marker data across a watershed; to compare these dynamics to fecal indicator counts, general measurements of water quality, and climatic forces; and to identify geographic areas of intense exposure to specific sources of contamination. Samples were collected during a 2-year period in the Tillamook basin in Oregon at 30 sites along five river tributaries and in Tillamook Bay. We performed Bacteroidales PCR assays with general, ruminant-source-specific, and human-source-specific primers to identify fecal sources. We determined the Escherichia coli most probable number, temperature, turbidity, and 5-day precipitation. Climate and water quality data collectively supported a rainfall runoff pattern for microbial source input that mirrored the annual precipitation cycle. Fecal sources were statistically linked more closely to ruminants than to humans; there was a 40% greater probability of detecting a ruminant source marker than a human source marker across the basin. On a sample site basis, the addition of fecal source tracking data provided new information linking elevated fecal indicator bacterial loads to specific point and nonpoint sources of fecal pollution in the basin. Inconsistencies in E. coli and host-specific marker trends suggested that the factors that control the quantity of fecal indicators in the water column are different than the factors that influence the presence of Bacteroidales markers at specific times of the year. This may be important if fecal indicator counts are used as a criterion for source loading potential in receiving waters.

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.

We used genome fragment enrichment and bioinformatics to identify several microbial DNA sequences with high potential for use as markers in PCR assays for detection of human fecal contamination in water. Following competitive solution-phase hybridization of total DNA from human and pig fecal samples, 351 plasmid clones were sequenced and were determined to define 289 different genomic DNA regions. These putative human-specific fecal bacterial DNA sequences were then analyzed by dot blot hybridization, which confirmed that 98% were present in the source human fecal microbial community and absent from the original pig fecal DNA extract. Comparative sequence analyses of these sequences suggested that a large number (43.5%) were predicted to encode bacterial secreted or surface-associated proteins. Deoxyoligonucleotide primers capable of annealing to a subset of 26 of the candidate sequences predicted to encode factors involved in interactions with host cells were then used in the PCR and did not amplify markers in DNA from any additional pig fecal specimens. These 26 PCR assays exhibited a range of specificity in tests with 11 other animal sources, with more than half amplifying markers only in specimens from dogs or cats. Four assays were more specific, detecting markers only in specimens from humans, including those from 18 different human populations examined. We then demonstrated the potential utility of these assays by using them to detect human fecal contamination in several impacted watersheds. [ABSTRACT FROM AUTHOR]

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

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. [ABSTRACT FROM AUTHOR]

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

Exposure to feces in two watersheds with different management histories was assessed by tracking cattle feces bacterial populations using multiple host-specific PCR assays. In addition, environmental factors affecting the occurrence of these markers were identified. Each assay was performed using DNA extracts from water and sediment samples collected from a watershed directly impacted by cattle fecal pollution (WS1) and from a watershed impacted only through runoff (WS2). In WSI, the ruminant-specific Bacteroidales 16S rRNA gene marker CF128F was detected in 65% of the water samples, while the non-16S rRNA gene markers Bad, Bac2, and Bac5 were found in 32 to 37% of the water samples. In contrast, all source-specific markers were detected in less than 6% of the water samples from WS2. Binary logistic regressions (BLRs) revealed that the occurrence of Bac32F and CF128F was significantly correlated with season as a temporal factor and watershed as a site factor. BLRs also indicated that the dynamics of fecal-source-tracking markers correlated with the density of a traditional fecal indicator (P < 0.001). Overall, our results suggest that a combination of 16S rRNA gene and non-16S rRNA gene markers provides a higher level of confidence for tracking unknown sources of fecal pollution in environmental samples. This study also provided practical insights for implementation of microbial source-tracking practices to determine sources of fecal pollution and the influence of environmental variables on the occurrence of source-specific markers. [ABSTRACT FROM AUTHOR]

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