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

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

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

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

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

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

Quantitative CrAssphage PCR Assays for Human Fecal Pollution Measurement.

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

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.

Identification of Specialists and Abundance-Occupancy Relationships among Intestinal Bacteria of Aves, Mammalia, and Actinopterygii.

The coalescence of next-generation DNA sequencing methods, ecological perspectives, and bioinformatics analysis tools is rapidly advancing our understanding of the evolution and function of vertebrate-associated bacterial communities. Delineation of host-microbe associations has applied benefits ranging from clinical treatments to protecting our natural waters. Microbial communities follow some broad-scale patterns observed for macroorganisms, but it remains unclear how the specialization of intestinal vertebrate-associated communities to a particular host environment influences broad-scale patterns in microbial abundance and distribution. We analyzed the V6 region of 16S rRNA genes amplified from 106 fecal samples spanning Aves, Mammalia, and Actinopterygii (ray-finned fish). We investigated the interspecific abundance-occupancy relationship, where widespread taxa tend to be more abundant than narrowly distributed taxa, among operational taxonomic units (OTUs) within and among host species. In a separate analysis, we identified specialist OTUs that were highly abundant in a single host and rare in all other hosts by using a multinomial model without excluding undersampled OTUs a priori. We show that intestinal microbes in humans and other vertebrates display abundance-occupancy relationships, but because intestinal host-associated communities have undergone intense specialization, this trend is violated by a disproportionately large number of specialist taxa. Although it is difficult to distinguish the effects of dispersal limitations, host selection, historical contingency, and stochastic processes on community assembly, results suggest that intestinal bacteria can be shared among diverse hosts in ways that resemble the distribution of "free-living" bacteria in the extraintestinal environment.

Comparison of Sewage and Animal Fecal Microbiomes by Using Oligotyping Reveals Potential Human Fecal Indicators in Multiple Taxonomic Groups.

Most DNA-based microbial source tracking (MST) approaches target host-associated organisms within the order Bacteroidales, but the gut microbiota of humans and other animals contain organisms from an array of other taxonomic groups that might provide indicators of fecal pollution sources. To discern between human and nonhuman fecal sources, we compared the V6 regions of the 16S rRNA genes detected in fecal samples from six animal hosts to those found in sewage (as a proxy for humans). We focused on 10 abundant genera and used oligotyping, which can detect subtle differences between rRNA gene sequences from ecologically distinct organisms. Our analysis showed clear patterns of differential oligotype distributions between sewage and animal samples. Over 100 oligotypes of human origin occurred preferentially in sewage samples, and 99 human oligotypes were sewage specific. Sequences represented by the sewage-specific oligotypes can be used individually for development of PCR-based assays or together with the oligotypes preferentially associated with sewage to implement a signature-based approach. Analysis of sewage from Spain and Brazil showed that the sewage-specific oligotypes identified in U.S. sewage have the potential to be used as global alternative indicators of human fecal pollution. Environmental samples with evidence of prior human fecal contamination had consistent ratios of sewage signature oligotypes that corresponded to the trends observed for sewage. Our methodology represents a promising approach to identifying new bacterial taxa for MST applications and further highlights the potential of the family Lachnospiraceae to provide human-specific markers. In addition to source tracking applications, the patterns of the fine-scale population structure within fecal taxa suggest a fundamental relationship between bacteria and their hosts.

Age-related shifts in the density and distribution of genetic marker water quality indicators in cow and calf feces.

Calves make up about 16% of the current bovine population in the United States and can excrete high levels of human pathogens in their feces. We describe the density and distribution of genetic markers from 9 PCR- and real-time quantitative PCR-based assays, including CF128, CF193, CowM2, CowM3, GenBac3, Entero1, EC23S857, CampF2, and ttr-6, commonly used to help assess ambient surface water quality. Each assay was tested against a collection of 381 individual bovine fecal samples representing 31 mother and calf pairings collected over a 10-month time period from time of birth through weaning. Genetic markers reported to be associated with ruminant and/or bovine fecal pollution were virtually undetected in calves for up to 115 days from birth, suggesting that physiological changes in calf ruminant function impact host-associated genetic marker shedding. In addition, general fecal indicator markers for Bacteroidales, Escherichia coli, and Enterococcus spp. exhibited three separate trends across time, indicating that these bacteria respond differently to age-related physiological and dietary changes during calf development. The results of this study suggest that currently available PCR-based water quality indicator technologies can under- or overestimate fecal pollution originating from calves and identify a need for novel calf-associated source identification methods.

Biotic interactions and sunlight affect persistence of fecal indicator bacteria and microbial source tracking genetic markers in the upper Mississippi river.

The sanitary quality of recreational waters that may be impacted by sewage is assessed by enumerating fecal indicator bacteria (FIB) (Escherichia coli and enterococci); these organisms are found in the gastrointestinal tracts of humans and many other animals, and hence their presence provides no information about the pollution source. Microbial source tracking (MST) methods can discriminate between different pollution sources, providing critical information to water quality managers, but relatively little is known about factors influencing the decay of FIB and MST genetic markers following release into aquatic environments. An in situ mesocosm was deployed at a temperate recreational beach in the Mississippi River to evaluate the effects of ambient sunlight and biotic interactions (predation, competition, and viral lysis) on the decay of culture-based FIB, as well as molecularly based FIB (Entero1a and GenBac3) and human-associated MST genetic markers (HF183 and HumM2) measured by quantitative real-time PCR (qPCR). In general, culturable FIB decayed the fastest, while molecularly based FIB and human-associated genetic markers decayed more slowly. There was a strong correlation between the decay of molecularly based FIB and that of human-associated genetic markers (r(2), 0.96 to 0.98; P < 0.0001) but not between culturable FIB and any qPCR measurement. Overall, exposure to ambient sunlight may be an important factor in the early-stage decay dynamics but generally was not after continued exposure (i.e., after 120 h), when biotic interactions tended to be the only/major influential determinant of persistence.

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.

Development of rapid canine fecal source identification PCR-based assays.

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

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

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

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

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

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.

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

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

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

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

Sewage reflects the distribution of human faecal Lachnospiraceae.

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

Differential decay of enterococci and Escherichia coli originating from two fecal pollution sources.

Using in situ subtropical aquatic mesocosms, fecal source (cattle manure versus sewage) was shown to be the most important contributor to differential loss in viability of fecal indicator bacteria (FIB), specifically enterococci in freshwater and Escherichia coli in marine habitats. In this study, sunlight exposure and indigenous aquatic microbiota were also important contributors, whose effects on FIB also differed between water types.

Comparison of the microbial community structures of untreated wastewaters from different geographic locales.

Microbial sewage communities consist of a combination of human fecal microorganisms and nonfecal microorganisms, which may be residents of urban sewer infrastructure or flowthrough originating from gray water or rainwater inputs. Together, these different microorganism sources form an identifiable community structure that may serve as a signature for sewage discharges and as candidates for alternative indicators specific for human fecal pollution. However, the structure and variability of this community across geographic space remains uncharacterized. We used massively parallel 454 pyrosequencing of the V6 region in 16S rRNA genes to profile microbial communities from 13 untreated sewage influent samples collected from a wide range of geographic locations in the United States. We obtained a total of 380,175 high-quality sequences for sequence-based clustering, taxonomic analyses, and profile comparisons. The sewage profile included a discernible core human fecal signature made up of several abundant taxonomic groups within Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria. DNA sequences were also classified into fecal, sewage infrastructure (i.e., nonfecal), and transient groups based on data comparisons with fecal samples. Across all sewage samples, an estimated 12.1% of sequences were fecal in origin, while 81.4% were consistently associated with the sewage infrastructure. The composition of feces-derived operational taxonomic units remained congruent across all sewage samples regardless of geographic locale; however, the sewage infrastructure community composition varied among cities, with city latitude best explaining this variation. Together, these results suggest that untreated sewage microbial communities harbor a core group of fecal bacteria across geographically dispersed wastewater sewage lines and that ambient water quality indicators targeting these select core microorganisms may perform well across the United States.

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

Municipal stormwater systems are designed to collect, transport, and discharge precipitation from a defined catchment area into local surface waters. However, these discharges may contain unsafe levels of fecal waste. Paired measurements of Escherichia coli, precipitation, three land use metrics determined by geographic information system (GIS) mapping, and host-associated genetic markers indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), dog (DG3), and avian (GFD) fecal sources were assessed in 231 urban stream samples impacted by two or more municipal stormwater outfalls. Receiving water samples were collected twice per month (n = 24) and after rain events (n = 9) from seven headwaters of the Anacostia River in the District of Columbia (United States) exhibiting a gradient of impervious surface, residential, and park surface areas. Almost 50% of stream samples (n = 103) were impaired, exceeding the local E. coli single sample maximum assessment level (410 MPN/100 ml). Fecal scores (average log10 copies per 100 ml) were determined to prioritize sites by pollution source and to evaluate potential links with land use, rainfall, and E. coli levels using a recently developed censored data analysis approach. Dog, ruminant, and avian fecal scores were almost always significantly increased after rain or when E. coli levels exceeded the local benchmark. Human fecal pollution trends showed the greatest variability with detections ranging from 9.1% to 96.7% across sites. Avian fecal scores exhibited the closest connection to land use, significantly increasing in catchments with larger residential areas after rain events (p = 0.038; R2 = 0.62). Overall, results demonstrate that combining genetic fecal source identification methods with GIS mapping complements routine E. coli monitoring to improve management of urban streams impacted by stormwater outfalls.