Microbial Source Tracking Methods Research Articles

Comparing Microbial Source Tracking Methods for Precision and Reliability

Microbial source tracking is a valuable tool in forensic science, specifically in the analysis of trace evidence. Numerous tools have been developed to estimate the proportion of different contamination sources within a mixture. In this study, we evaluate the accuracy of various source tracking methods using datasets from microbiome studies. In addition to assessing source tracking methods, we also incorporate two widely used cell type deconvolution methods, namely EPIC and PREDE, which are designed to identify missing cell types in a given dataset. Furthermore, we investigate the effectiveness of combined methods by integrating RAD, a source tracking method aimed at filtering out unimportant sources, with either EPIC or PREDE for enhanced accuracy in both source tracking and cell type deconvolution. This research represents a pioneering effort to examine the application of cell type deconvolution methods in source tracking and vice versa. Particularly noteworthy is our focus on scenarios involving missing sources or cell types in the reference data, shedding light on the intricate interplay between these two analytical domains.

Occurrence and removal of fecal bacteria and microbial source tracking markers in a stormwater detention basin overlying the Edwards Aquifer recharge zone in Texas.

The Edwards Aquifer is the primary water resource for over 2 million people in Texas and faces challenges including fecal contamination of water recharging the aquifer, while effectiveness of best management practices (BMPs) such as detention basins in mitigating fecal pollution remains poorly understood. For this study, the inlet and outlet of a detention basin overlying the aquifer's recharge zone were sampled following storm events using automated samplers. Microbial source tracking and culture-based methods were used to determine the occurrence and removal of fecal genetic markers and fecal coliform bacteria in collected water samples. Markers included E. coli (EC23S857), Enterococcus (Entero1), human (HF183), canine (BacCan), and bird (GFD). Fecal coliforms, EC23S857, and Entero1 were detected following each storm event. GFD was the most frequent host-associated marker detected (91% of samples), followed by BacCan (46%), and HF183 (17%). Wilcoxon signed rank tests indicated significantly lower outlet concentrations for fecal coliforms, EC23S857, and Entero1, but not for HF183, GFD, and BacCan. Higher GFD and BacCan outlet concentrations may be due to factors independent of basin design, such as the non-point source nature of bird fecal contamination and domestic dog care practices in neighborhoods contributing to the basin. Mann-Whitney tests showed marker concentrations were not significantly higher during instances of fecal coliform water quality criterion exceedance, except for E. coli, and that fecal coliform concentrations were not significantly different based on marker detection. Overall, results suggest that the detention basin is effective in attenuating fecal contamination associated with fecal coliforms and the general markers, but not for host-associated markers. Consequently, management efforts should focus on mitigating dog and bird-associated fecal pollution in the study region.

Cross-method assessment of coliphage detection methods in the framework of EPA regulatory standards.

This study aimed to understand the performance and utility of US EPA-approved coliphage methods in comparison to fecal indicator bacteria (FIB) and molecular microbial source tracking (MST) methods in recreational waters. We used US EPA Method 1642 to quantify concentrations of coliphage along with culture- and molecular-based enumeration of E. coli and Enterococcus sp, and human fecal source marker HF183. We also conducted a feasibility assessment to determine the utility of US EPA Method 1642 for application to routine recreational water monitoring. Ten sampling events were conducted at three sampling sites over the duration of a year. Average concentrations of somatic (SC) (log10 1.48 PFU/100 mL) and male-specific (MSC) coliphages (log10 1.00 PFU/100 mL) at all sites were low with SC found across a broader range (0.3-3.1 log10 PFU/100 mL) of concentrations compared to MSC (non-detect-1.7 log10 PFU/100 mL). A feasibility assessment was conducted across US EPA Method 1642 for coliphage enumeration, culture-based FIB, defined substrate technology (DST) approaches Enterolert™ and Colilert®, and quantitative microbial source tracking (qMST) US EPA Method 1696. US EPA Method 1642 had the longest processing times, but also was moderate in cost, compared to the DST and qMST molecular methods. Given the poor correlations between MSC and SC with FIB and qMST markers in this study and the cumbersome nature of US EPA Method 1642, the method may not be the most applicable method for use in systems impacted predominantly by stormwater and other non-point source pollution. Findings from this study, however, provide guidance on the application of fecal indicator virus in ambient coastal surface waters.

Ecological dynamics imposes fundamental challenges in community‐based microbial source tracking

AbstractQuantifying the contributions of possible environmental sources (“sources”) to a specific microbial community (“sink”) is a classical problem in microbiology known as microbial source tracking (MST). Solving the MST problem will not only help us understand how microbial communities were formed, but also have far‐reaching applications in pollution control, public health, and forensics. MST methods generally fall into two categories: target‐based methods (focusing on the detection of source‐specific indicator species or chemicals); and community‐based methods (using community structure to measure similarity between sink samples and potential source environments). As next‐generation sequencing becomes a standard community‐assessment method in microbiology, numerous community‐based computational methods, referred to as MST solvers hereafter have been developed and applied to various real datasets to demonstrate their utility across different contexts. Yet, those MST solvers do not consider microbial interactions and priority effects in microbial communities. Here, we revisit the performance of several representative MST solvers. We show compelling evidence that solving the MST problem using existing MST solvers is impractical when ecological dynamics plays a role in community assembly. In particular, we clearly demonstrate that the presence of either microbial interactions or priority effects will render the MST problem mathematically unsolvable for MST solvers. We further analyze data from fecal microbiota transplantation studies, finding that the state‐of‐the‐art MST solvers fail to identify donors for most of the recipients. Finally, we perform community coalescence experiments to demonstrate that the state‐of‐the‐art MST solvers fail to identify the sources for most of the sinks. Our findings suggest that ecological dynamics imposes fundamental challenges in MST. Interpretation of results of existing MST solvers should be done cautiously.

Campylobacter Species, Microbiological Source Tracking and Risk Assessment of Bacterial pathogens

Campylobacter species continue to remain critical pathogens of public health interest. They are responsible for approximately 500 million cases of gastroenteritis per year worldwide. Infection occurs through the consumption of contaminated food and water. Microbial risk assessment and source tracking are crucial epidemiological strategies to monitor the outbreak of campylobacteriosis effectively. Various methods have been proposed for microbial source tracking and risk assessment, most of which rely on conventional microbiological techniques such as detecting fecal indicator organisms and other novel microbial source tracking methods, including library-dependent microbial source tracking and library-independent source tracking approaches. However, both the traditional and novel methods have their setbacks. For example, while the conventional techniques are associated with a poor correlation between indicator organism and pathogen presence, on the other hand, it is impractical to interpret qPCR-generated markers to establish the exact human health risks even though it can give information regarding the potential source and relative human risk. Therefore, this article provides up-to-date information on campylobacteriosis, various approaches for source attribution, and risk assessment of bacterial pathogens, including next-generation sequencing approaches such as shotgun metagenomics, which effectively answer the questions of potential pathogens are there and in what quantities.

Persistence of Fecal Indicators and Microbial Source Tracking Markers in Water Flushed from Riverbank Soils

Sewer overflows and exfiltration can potentially contaminate water bodies with pathogens from wastewater. Microbial source tracking (MST) methods such as the detection of the HF183 gene target of Bacteroides have been proposed to monitor human fecal pollution inputs to surface waters; however, the persistence of HF183 and other MST markers in water flushed from soils after contamination events is not well understood. In this study, the persistence and decay of two culture-based fecal indicators, Escherichia coli and enterococci, and two molecular MST markers, HF183 and pepper mild mottle virus (PMMoV), were evaluated in riverbank soils spiked with untreated sewage, which were left idle for 1, 14, 28, 60, and 121 days under dark conditions and then flushed with synthetic rainwater. All four microbial indicators were still detected in flush water 4 months after the soil was contaminated. PMMoV persisted much longer and had a slower decay rate than the other microbial indicators, and E. coli degraded most rapidly. In consecutive flushing experiments with fresh (1 day) sewage-spiked soils, HF183, E. coli, and enterococci were all detected after 20 consecutive flushes with rainwater, but PMMoV was not detected after the fifth flush. Our findings indicate that water (e.g., stormwater interflow) flushing through riverbank soils that have previously been contaminated by sewer overflows or sewer exfiltration can potentially be a source of microbial pollution to surface waters, even for several months after the contamination occurs. Results from this study also demonstrate the benefits of using multiple human-associated fecal indicators to distinguish pollution from different microbial groups in water bodies.Graphical abstract

Enteric pathogens and Carbapenem resistance genes are widespread in the fecal contaminated soils of cattle farms in the United States

Cattle farming is considered a major contributor to antibiotic resistant (AR) genes and bacteria in nearby environments, predominantly due to the large amount of manure released by cattle to soils. This study sought to compare soil within and outside of cattle pens from seven farms in the US. Soil microbial community differences are described, as well as differences in AR gene and enteric pathogen concentrations in the soils. Sources of fecal loading are quantified via microbial source tracking (MST) methods. The family Peptostreptococcaceae was more abundant in pen soils, and Rhodanobacteraceae was more abundant in non-pen soils. There were no differences in microbial community diversity between soils within and outside of cattle pens. The MST result showed that ruminant-specific fecal contamination (Rum2Bac) was abundant both in pen and non-pen soils, likely indicating heavy cattle fecal loading. However, the soil within cattle pens had higher levels of Campylobacter, Salmonella, and AR genes for resistance to sulfonamides (sul1) and carbapenems (KPC) than the soil outside of pens (p<0.05). This is the first study identifying KPC in livestock-associated soils in the US. This study supports increased hazard associated with livestock soils for animal and human health, as well as environmental quality.

Microbial Source Tracking Approach to Investigate Fecal Waste at the Strawberry Creek Watershed and Clam Beach, California, USA.

Clam Beach is located in Northern California, USA, and is listed as an impaired waterway by the federal government. The scope of this study was to investigate this beach and surrounding watershed to determine, if possible, the source of the impairment by conducting an 11-h beach study and 8-week watershed study. We used traditional fecal indicator bacteria (FIB) and microbial source tracking (MST) methods to help identify source(s) of the FIB. Our study was focused on four possible contributors: human, ruminant, canine, and bird. A total of 169 samples were collected, analyzed, and compared to the California Department of Health single sample maximum (SSM) objective. In the beach study, 29 (44%) samples exceeded at least one SSM objective, which would have resulted in a resample per state regulations for recreational primary contact use. MST methods showed that the most abundant marker detected was bird, in 65% of the samples, but varied by sample location, which is likely due to a natural population of nearshore birds regularly observed along Clam Beach. The watershed study highlighted the potential influence from ruminants throughout the region, while humans did not appear to be a significant contributor. Health risk to humans appears to be low.

Synergistic Application of Molecular Markers and Community-Based Microbial Source Tracking Methods for Identification of Fecal Pollution in River Water During Dry and Wet Seasons.

It is important to track fecal sources from humans and animals that negatively influence the water quality of rural rivers and human health. In this study, microbial source tracking (MST) methods using molecular markers and the community-based FEAST (fast expectation–maximization microbial source tracking) program were synergistically applied to distinguish the fecal contributions of multiple sources in a rural river located in Beijing, China. The performance of eight markers were evaluated using 133 fecal samples based on real-time quantitative (qPCR) technique. Among them, six markers, including universal (BacUni), human-associated (HF183-1 and BacH), swine-associated (Pig-2-Bac), ruminant-associated (Rum-2-Bac), and avian-associated (AV4143) markers, performed well in the study. A total of 96 water samples from the river and outfalls showed a coordinated composition of fecal pollution, which revealed that outfall water might be a potential input of the Fsq River. In the FEAST program, bacterial 16S rRNA genes of 58 fecal and 12 water samples were sequenced to build the “source” library and “sink,” respectively. The relative contribution (<4.01% of sequence reads) of each source (i.e., human, swine, bovine, or sheep) was calculated based on simultaneous screening of the operational taxonomic units (OTUs) of sources and sinks, which indicated that community-based MST methods could be promising tools for identifying fecal sources from a more comprehensive perspective. Results of the qPCR assays indicated that fecal contamination from human was dominant during dry weather and that fecal sources from swine and ruminant were more prevalent in samples during the wet season than in those during the dry season, which were consistent with the findings predicted by the FEAST program using a very small sample size. Information from the study could be valuable for the development of improved regulation policies to reduce the levels of fecal contamination in rural rivers.

Characterization of Stormwater Runoff Based on Microbial Source Tracking Methods.

Rainfall and associated urban runoff have been linked to an increased deterioration of environmental waters, carrying several pollutants including pathogenic microorganisms. Such happens because fecal matter is washed into storm drainage pipes that are afterward released into environmental waters. Stormwater has not been extensively characterized as it is, because most studies are performed either on drainage pipes that are often impacted by sewage leakage or directly in environmental waters following a rain event. In this study, stormwater collected directly from the streets, was monitored for the presence of fecal indicator bacteria (FIB) and three potential important sources of fecal contamination in urban environments (human, cats, and dogs) in three distinct basins in Lisbon, Portugal. Stormwater was collected in sterilized plastic boxes inserted in the storm drains, therefore collecting only runoff. High concentration of fecal contamination was detected with a high percentage of the samples displayed at least one source of contamination. A strong relationship was found between the number of detected sources and the precipitation levels. Although no statistical correlation was found between the locations and the presence of FIB or source markers, the results show a trend in geographical information on the type of urban use in each basin. To the best of our knowledge, this is the first study analyzing the runoff collected directly from the streets. This study suggests that, in urban areas, stormwater runoff is highly impacted by fecal matter, not only from domestic animals but also from human origin, before any cross-contamination in the drainage system and may, by itself, pose a high risk to human health and the environment, particularly if water reuse of this water without further disinfection treatment is the final goal.

Microbial source tracking using metagenomics and other new technologies.

The environment is under siege from a variety of pollution sources. Fecal pollution is especially harmful as it disperses pathogenic bacteria into waterways. Unraveling origins of mixed sources of fecal bacteria is difficult and microbial source tracking (MST) in complex environments is still a daunting task. Despite the challenges, the need for answers far outweighs the difficulties experienced. Advancements in qPCR and next generation sequencing (NGS) technologies have shifted the traditional culture-based MST approaches towards culture independent technologies, where community-based MST is becoming a method of choice. Metagenomic tools may be useful to overcome some of the limitations of community-based MST methods as they can give deep insight into identifying host specific fecal markers and their association with different environments. Adoption of machine learning (ML) algorithms, along with the metagenomic based MST approaches, will also provide a statistically robust and automated platform. To compliment that, ML-based approaches provide accurate optimization of resources. With the successful application of ML based models in disease prediction, outbreak investigation and medicine prescription, it would be possible that these methods would serve as a better surrogate of traditional MST approaches in future.

Assessing the faecal source sensitivity and specificity of ruminant and human genetic microbial source tracking markers in the central Ethiopian highlands

This study tested genetic microbial source tracking (MST) methods for identifying ruminant‐ (BacR) and human‐associated (HF183/BacR287, BacHum) bacterial faecal contaminants in Ethiopia in a newly created regional faecal sample bank (n = 173). BacR performed well, and its marker abundance was high (100% sensitivity (Sens), 95% specificity (Spec), median log10 8·1 marker equivalents (ME) g−1 ruminant faeces). Human‐associated markers tested were less abundant in individual human samples (median: log10 5·4 and 4·2 (ME + 1) g−1) and were not continuously detected (81% Sens, 91% Spec for BacHum; 77% Sens, 91% Spec for HF183/BacR287). Furthermore, the pig‐associated Pig2Bac assay was included and performed excellent (100% Sens, 100% Spec). To evaluate the presence of MST targets in the soil microbiome, representative soil samples were tested during a whole seasonal cycle (n = 60). Only BacR could be detected, but was limited to the dry season and to sites of higher anthropogenic influence (log10 3·0 to 4·9 (ME + 1) g−1 soil). In conclusion, the large differences in marker abundances between target and non‐target faecal samples (median distances between distributions ≥log10 3 to ≥log10 7) and their absence in pristine soil indicate that all tested assays are suitable candidates for diverse MST applications in the Ethiopian area.

Identifying septic pollution exposure routes during a waterborne norovirus outbreak - A new application for human-associated microbial source tracking qPCR

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

Seasonal influences on the use of genetic markers as performance indicators for small wastewater treatment plants

The development of microbial source tracking methods has resulted in an array of genetic faecal markers for assessing human health risks posed from surface water pollution. However, their use as performance metrics at wastewater treatment plants (WWTPs) has not been explored extensively. Here we compared three Bacteroides (HF183, HumM2, AllBac) and two E. coli (H8, RodA) genetic markers for summer and winter performance monitoring at twelve small rural (<250 PE) and three larger WWTPs in NE England. Small WWTPs are of interest because they are poorly understood and their impact on surface water quality may be underestimated. Overall, genetic marker data showed significant differences in treatment performance at smaller versus larger WWTPs. For example, effluent abundances of HF183 and HumM2 were significantly higher in smaller systems (p = 0.003 for HumM2; p = 0.02 for HF183). Genetic markers also showed significant differences in performance between seasons (p < 0.01, n = 120), with human-specific markers (i.e., HF183, HumM2, H8) being generally better for summer WWTP monitoring. In contrast, Bacteroides markers were much more suitable for winter monitoring, possibly because the E. coli markers are less sensitive to differences in temperature and sunlight conditions. Overall, Bacteroides markers best described WWTP treatment performance across all samples, although seasonal differences suggest caution is needed when markers are used for performance monitoring. Genetic markers definitely provide rapid and new information about WWTP performance, but more spatially diverse studies are needed to refine their use for routine WWTP monitoring.

Comparative fate of CrAssphage with culturable and molecular fecal pollution indicators during activated sludge wastewater treatment

Wastewater treatment plants are typically monitored using fecal indicator bacteria to ensure adequate microbial water quality of the treated effluent. Fecal indicator bacteria exhibit poor correlation with virus fate in the environment, including during wastewater treatment. Viral-based microbial source tracking methods have the potential to overcome this limitation. The recently discovered human gut bacteriophage crAssphage is a promising viral human fecal indicator. In this current study, primary influent, primary effluent, secondary effluent, and final effluent of a conventional activated sludge wastewater treatment plant were analyzed for a suite of fecal indicators to evaluate the suitability of crAssphage as a wastewater process indicator for virus removal. CrAssphage was the most abundant fecal indicator measured through the wastewater treatment process. Culturable and molecular bacterial fecal pollution indicators showed higher removal than viral fecal pollution indicators, including crAssphage, confirming the necessity of a viral-specific fecal monitoring target. CrAssphage was strongly correlated with adenovirus and polyomavirus molecular indicators through the wastewater treatment process. Literature comparison demonstrated site-specific removal of molecular fecal indicators during wastewater treatment highlighting the need for local performance validation. The high abundance of crAssphage and correlation with pathogenic viruses suggests the potential suitability of crAssphage as a viral fecal pollution process indicator during wastewater treatment.

Source identification of antibiotic resistance genes in a peri-urban river using novel crAssphage marker genes and metagenomic signatures

Antimicrobial resistance is a growing public health concern, and environment is regarded as an important reservoir and dissemination route for antibiotic resistance genes (ARGs). To prevent and control ARG pollution, it is essential to correctly disentangle source-sink relationship of ARGs in the environment. However, accurately apportioning sources of ARGs is still a big challenge due to the complex interaction of multiple sources and contaminants in the environment with changing dynamics. In this study, we addressed this problem and focused on identifying the potential sources of ARGs in a peri-urban river by jointly utilizing two novel microbial source tracking methods. To attain the objective, sediment/water samples were collected from the peri-urban river and four ARG-associated ecotypes including effluents of sewage treatment plants (STPs), STP influent, chicken manures and pig manures. The high-throughput profilings of ARGs and microbial taxa in the river sediments and the four ecotypes were comprehensively characterized in combination of shotgun sequencing and metagenomic assembly analysis. CrAssphage, a recently-discovered DNA bacteriophage, was employed to track the impact of human fecal pollution on ARGs in the river sediments. Further, SourceTracker, a machine-learning classification tool, was used for quantifying the contributions of potential sources to ARGs in the river sediments based on the metagenomic signatures of ARGs and microbial taxa. In total, 888 ARG subtypes belonging to 29 ARG types were detected across all samples, including mcr-1 and a range of carbapenemases types. Statistical analyses suggested different ecotypes generally had distinct profiles of both ARGs and microbial taxa, while the ARG compositions were significantly correlated with the microbial community. Source tracking with crAssphage showed the presence of ARGs in the river sediments might be largely impacted by the extent of human fecal pollution, which was also confirmed by the analyses of SourceTracker that the discharge from STPs was the largest contributor of ARGs (81.6–92.1%) and microbes (49.3–68.1%) in the river sediments. Results of the study can help us to better understand the characterization of ARGs in the peri-urban ecosystem and to design effective prevention and control strategies for reducing ARG dissemination.

Microbial Source Tracking Using 16S rRNA Amplicon Sequencing Identifies Evidence of Widespread Contamination from Young Children's Feces in an Urban Slum of Nairobi, Kenya.

Child exposure to fecal contamination remains common in low- and middle-income countries after sanitation interventions. Unsafe disposal of children's feces may contribute to this continued exposure, but its relative importance to domestic fecal contamination is not well understood. To address this gap, we interviewed and collected environmental samples (drinking water, caregiver hands, child hands, surfaces, soil, open drainage ditches, standing water, streams) from 40 households in Kibera, an urban slum in Nairobi, Kenya. To track young children's feces (<3 years old) separately from other human-associated fecal sources, we validated distance-based and Bayesian (SourceTracker) microbial source tracking methods using amplicon-based sequencing of the 16S rRNA gene. Contamination by young children's feces could be identified and distinguished separately from older child/adult feces with high sensitivity and specificity in water and soil. Among environmental samples, young children's feces were almost always identified as the dominant source of human fecal contamination inside households (hands, surfaces) whereas older children/adult feces were often identified as the dominant source outside households (standing water, streams, soil). Markers for young children's feces were also detected in standing water and streams, and markers for both fecal sources were equally likely to be dominant in open ditches. These results establish motivation for sanitation interventions that directly address child feces management.

Detection of a microbial source tracking marker by isothermal helicase-dependent amplification and a nucleic acid lateral-flow strip test

Over the last decades, various PCR-based methods have been proposed that can identify sources of faecal pollution in environmental waters. These microbial source tracking (MST) methods are powerful tools to manage water quality and support public health risk assessment. However, their application is limited by the lack of specialized equipment and trained personnel in laboratories performing microbiological water quality assessment. Here, we describe a novel molecular method that combines helicase-dependent amplification (HDA) with a strip test for detecting ruminant faecal pollution sources. Unlike quantitative PCR (qPCR), the developed HDA-strip assay only requires a heating block to amplify the ruminant-associated Bacteroidetes 16S rRNA marker (BacR). Following HDA, the reaction mixture can be directly applied onto the test strip, which detects and displays the amplification products by marker-specific hybridization probes via an on-strip colorimetric reaction. The entire assay takes two hours and demands no extensive practical training. Furthermore, the BacR HDA-strip assay achieved comparable results in head-to-head performance tests with the qPCR reference, in which we investigated source-sensitivity and source-specificity, the analytical limit of detection, and the sample limit of detection. Although this approach only yields qualitative results, it can pave a way for future simple-to-use MST screening tools.

Fecal source tracking and eDNA profiling in an urban creek following an extreme rain event

Fecal contamination of recreational waters (i.e. lakes, rivers, beaches) poses an on-going problem for environmental and public health. Heavy rainfall can exacerbate existing problems with fecal contamination. As there could be variable sources of fecal contamination, identifying the source is critical for remediation efforts. This study utilized microbial source tracking (MST), chemical source tracking (CST) markers and environmental DNA (eDNA) metabarcoding to profile sampling areas and identify sources of fecal contamination in creek, stormwater outfall and beach sites in the Etobicoke Creek watershed (Toronto, ON). Water samples were collected before and immediately following an extreme rain event. MST and CST identified stormwater outfalls as an important source of human fecal contamination during dry and wet conditions. eDNA metabarcoding allowed for potential identification of additional sources of fecal contamination and provided additional evidence of human fecal contamination. The extreme rainfall event altered the eDNA profiles, causing creek and beach sites to reflect a greater diversity of mammal and bird eDNA sequences. The profiles provided by eDNA metabarcoding provide a proof of concept suggesting that eDNA metabarcoding can be a useful tool to complement MST and CST methods for profiling sources of fecal contamination and studying impacts of extreme rain events.

Enterococcal Concentrations in a Coastal Ecosystem Are a Function of Fecal Source Input, Environmental Conditions, and Environmental Sources.

Fecal pollution at coastal beaches requires management efforts to address public health and economic concerns. Feces-borne bacterial concentrations are influenced by different fecal sources, environmental conditions, and ecosystem reservoirs, making their public health significance convoluted. In this study, we sought to delineate the influences of these factors on enterococcal concentrations in southern Maine coastal recreational waters. Weekly water samples and water quality measurements were conducted at freshwater, estuarine, and marine beach sites from June through September 2016. The samples were analyzed for total and particle-associated enterococcal concentrations, total suspended solids, and microbial source tracking markers (PCR: Bac32, HF183, CF128, DF475, and Gull2; quantitative PCR [qPCR]: AllBac, HF183, and GFD). Water, soil, sediment, and marine sediment samples were also subjected to 16S rRNA sequencing and SourceTracker analysis to determine the influence from these environmental reservoirs on water sample microbial communities. Enterococcal and particle-associated enterococcal concentrations were elevated in freshwater, but the concentrations of suspended solids were relatively similar. Mammal fecal contamination was significantly elevated in the estuary, with human and bird fecal contaminant levels similar between sites. A partial least-squares regression model indicated particle-associated enterococcal and mammal marker concentrations had the most significant positive relationships with enterococcal concentrations across marine, estuary, and freshwater environments. Freshwater microbial communities were significantly influenced by underlying sediment, while estuarine/marine beach communities were influenced by freshwater, high tide height, and estuarine sediment. Elevated enterococcal levels were reflective of a combination of increased fecal source input, environmental sources, and environmental conditions, highlighting the need for encompassing microbial source tracking (MST) approaches for managing water quality issues.IMPORTANCE Enterococci have long been the federal standard in determining water quality at estuarine and marine environments. Although enterococci are highly abundant in the intestines of many animals, they are not exclusive to that environment and can persist and grow outside fecal tracts. This presents a management problem for areas that are largely impaired by nonpoint source contamination, as fecal sources might not be the root cause of contamination. This study employed different microbial source tracking methods for delineating the influences from fecal source input, environmental sources, and environmental conditions to determine which combination of variables are influencing enterococcal concentrations in recreational waters at a historically impaired coastal town. The results showed that fecal source input, environmental sources, and conditions all play roles in influencing enterococcal concentrations. This highlights the need to include an encompassing microbial source tracking approach to assess the effects of all important variables on enterococcal concentrations.