Evaluation of molecular community analysis methods for discerning fecal sources and human waste

Influence of hydrological factors on bacterial community structure in a tropical monsoonal estuary in India

In the present study, we analyzed variations in bacterial community structure along a salinity gradient in a tropical monsoonal estuary (Cochin estuary [CE]), on the southwest coast of India, using Illumina next-generation sequencing (NGS). Water samples were collected from eight different locations thrice a year to assess the variability in the bacterial community structure and to determine the physico-chemical factors influencing the bacterial diversity. Proteobacteria was the most dominant phyla in the estuary followed by Bacteroidetes, Cyanobacteria, Actinobacteria, and Firmicutes. Statistical analysis indicated significant variations in bacterial communities between freshwater and mesohaline and euryhaline regions, as well as between the monsoon (wet) and nonmonsoon (dry) periods. The abundance of Betaproteobacteria was higher in the freshwater regions, while Alphaproteobacteria and Epsilonproteobactera were more abundant in mesohaline and euryhaline regions of the estuary. Gammaproteobacteria was more abundant in regions with high nutrient concentrations. Various bacterial genera indicating the presence of fecal contamination and eutrophication were detected. Corrplot based on Pearson correlation analysis demonstrated the important physico-chemical variables (temperature, salinity, dissolved oxygen, and inorganic nutrients) that influence the distribution of dominant phyla, class, and genera. The observed spatio-temporal variations in bacterial community structure in the CE were governed by regional variations in anthropogenic inputs and seasonal variations in monsoonal rainfall and tidal influx.

Identification the source of fecal contamination for geographically unassociated samples with a statistical classification model based on support vector machine

The bacterial diversity and corresponding biological significance revealed by high-throughput sequencing contribute massive information to source tracking of fecal contamination. The performances of classification models on predicting the fecal source of geographical local and foreign samples were examined herein, by applying support vector machine (SVM) algorithm. Random forest (RF) and Adaboost were applied for comparison as well. Discriminatory sequences were selected from Clostridiale, Bacteroidales, or Lactobacillales bacterial groups using extremely randomized trees (ExtraTrees). 1.51-12.64% of the unique sequences in the original library composed the representative markers, and they contributed 70% of the discrepancies between source microbiomes. The overall accuracy of the SVM model and the RF model on local samples was 96.08% and 98.04%, respectively, higher than that of the Adaboost (90.20%). As for the non-local samples, the SVM assigned most of the fecal samples into the correct category while several false-positive judgments occurred in closely related groups. The results in this paper suggested that the SVM was a time-saving and accurate method for fecal source tracking in contaminated water body with the potential capability of executing tasks based on geographically unassociated samples, and underlined the necessity of qPCR analysis for accurate detection of human source pollution.

Tracking Major Sources of Water Contamination Using Machine Learning

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

Identification of Penicillium verrucosum, Penicillium commune, and Penicillium crustosum Isolated from Chicken Eggs

Penicillium species belong to main causative agents of food spoilage leading to significant economic losses and potential health risk for consumers. These fungi have been isolated from various food matrices, including table eggs. In this study, both conventional Polymerase Chain Reaction (PCR) and Polymerase Chain Reaction-Internal Transcribed Spacer-Restriction Fragment Length Polymorphism (PCR-ITS-RFLP) methods were used for species identification of Penicillium (P.) spp. isolated from the eggshells of moldy chicken eggs. Seven restriction endonucleases (Bsp1286I, XmaI, HaeIII, HinfI, MseI, SfcI, Hpy188I) were applied to create ribosomal restriction patterns of amplified ITS regions. To identify P. verrucosum, P. commune, and P. crustosum with the help of conventional PCR assay, species-specific primer pairs VERF/VERR, COMF/COMR, and CRUF/CRUR were designed on the base of 5.8 subunit-Internal Transcribed Spacer (5.8S-ITS) region. Altogether, 121 strains of microscopic filamentous fungi were isolated by traditional culture mycological examination. After morphological evaluation of both macroscopic and microscopic features, 96 strains were classified in Penicillium spp. Two molecular methods used have confirmed eight isolates as P. verrucosum, 42 isolates as P. commune, and 19 isolates as P. crustosum. Both PCR-ITS-RFLP and conventional PCR assays appear to be suitable alternatives for rapid identification of the above mentioned Penicillium species.

Determining the primary sources of fecal pollution using microbial source tracking assays combined with land-use information in the Edwards Aquifer

The Edwards Aquifer serves as a primary source of drinking water to more than 2 million people in south-central Texas, and as a karst aquifer, is vulnerable to human and animal fecal contamination which poses a serious risk to human and environmental health. A one-year study (Jan 2018 - Feb 2019) was conducted to determine the primary sources of fecal pollution along the Balcones and Leon Creek within the Edwards Aquifer recharge and contributing zones using general (E. coli, enterococci, and universal Bacteriodales) and host-associated (human-, dog-, cow- and chicken/duck-associated Bacteriodales) microbial source tracking (MST) assays. Additionally, sites were classified based on surrounding land use as a potential source predictor and marker levels were correlated with rain events and water quality parameters. Levels for the three general indicators were highest and exhibited similar trends across the sampling sites, suggesting that the sole use of these markers is not sufficient for specific fecal source identification. Among the host-associated markers, highest concentrations were observed for the dog marker (BacCan) in the Leon Creek area and the cow marker (BacCow) in the Balcones Creek area. Additionally, Chicken/Duck-Bac, BacCan and BacCow all exhibited higher concentrations during the spring season and the end of fall/early winter. Relatively lower concentrations were observed for the human-associated markers (HF183 and BacHum), however, levels were higher in the Leon Creek area and highest following rainfall events. Additionally, relatively higher levels in HF183 and BacHum were observed at sites having greater human population and septic tank density and may be attributed to leaks or breaks in these infrastructures. This study is the first to examine and compare fecal contamination at rural and urban areas in the recharge and contributing zones of the Edwards Aquifer using a molecular MST approach targeting Bacteroidales 16S rRNA gene-based assays. The Bacteroidales marker assays, when combined with land use and weather information, can allow for a better understanding of the sources and fluxes of fecal contamination, which can help devise effective mitigation measures to protect water quality.

Application of the μAqua microarray for pathogenic organisms across a marine/freshwater interface

Monitoring drinking water quality is an important public health issue and pathogenic organisms present a particularly serious health hazard in freshwater bodies. However, many pathogenic bacteria, including cyanobacteria, and pathogenic protozoa can be swept into coastal lagoons and into near-shore marine environments where they continue to grow and pose a health threat to marine mammals and invertebrates. In this study, we tested the suitability of a phylochip (microarray for species detection) developed for freshwater pathogenic organisms to be applied to samples taken across a marine/freshwater interface at monthly intervals for two years. Toxic cyanobacteria and pathogenic protozoa were more numerous in a coastal lagoon than at the freshwater or marine site, indicating that this microarray can be used to detect the presence of these pathogens across a marine/freshwater interface and thus the potential for toxicity to occur within the entire watershed.

Combined microbial and isotopic signature approach to identify nitrate sources and transformation processes in groundwater

Nitrate (NO₃^-) pollution is a serious problem worldwide. Identification of NO₃^- sources and transformation processes in aquifers is a key step in effectively controlling and mitigating NO₃^- contamination. In this study, hydrochemical, microbial, and dual isotopic approaches were integrated to elucidate the sources and processes influencing NO₃^- contamination in the Pearl River Delta, China. The results showed a severe NO₃^- contamination, with 75% of the samples having NO₃^--N concentrations above the WHO standard of 10 mg L^-1. The δ¹⁵NNO₃^- and δ¹⁸ONO₃^- values and a multivariate statistical analysis of hydrochemical data both revealed that manure and sewage were mainly responsible for NO₃^- contamination. Biological indicators further demonstrated that, manure and sewage had greater impacts on groundwater quality during the rainy season than during the dry season. Based on the significant relationships of δ¹⁵NNO₃^- and δ¹⁸ONO₃^- with the logarithmic NO₃^- concentration (Ln(NO₃^-)), denitrification was confirmed to occur in the discharge zone during the rainy season. Proteobacteria, Bacteroidetes, and Planctomycetes were identified as the dominant phyla, and Dechloromonas, Flavobacterium, and Nitrospira were dominant among the denitrifying bacteria in groundwater. The abundance of denitrifying bacteria had significant positive correlations with δ¹⁵NNO₃^- and NO₂^--N during the rainy season, further confirming the occurrence of denitrification during the rainy season. This study showed that dual isotope techniques combined with microbial data can be a powerful tool for identifying the sources and microbial processes affecting NO₃^- in groundwater. Moreover, the results can provide useful insights for environmental managers to verify groundwater pollution and better apply remediation solutions.

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.

Application of high-throughput 16S rRNA sequencing to identify fecal contamination sources and to complement the detection of fecal indicator bacteria in rural groundwater

Residents in rural communities across Canada collect potable water from aquifers. Fecal contaminants from sewage and agricultural runoffs can penetrate aquifers, posing a public health risk. Standard methods for detecting fecal contamination test for fecal indicator bacteria (FIB), but the presence of these do not identify sources of contamination. In contrast, DNA-based diagnostic tools can achieve this important objective. We employed quantitative polymerase chain reaction (qPCR) and high-throughput DNA sequencing to trace fecal contamination sources in Wainfleet, a rural Ontario township that has been under the longest active boil water advisory in Canada due to FIB contamination in groundwater wells. Using traditional methods, we identified FIBs indicating persistent fecal pollution in well waters. We used 16S rRNA sequencing to profile groundwater microbial communities and identified Campylobacteraceae as a fecal contamination DNA marker in septic tank effluents (STEs). We also identified Turicibacter and Gallicola as a potential cow and chicken fecal contamination marker, respectively. Using human specific Bacteroidales markers, we identified leaking septic tanks as the likely primary fecal contamination source in some of Wainfleet's groundwater. Overall, the results support the use of sequencing-based methods to augment traditional water quality testing methods and help end-users assess fecal contamination levels and identify point and non-point pollution sources.

Fecal source tracking methods to elucidate critical sources of pathogens and contaminant microbial transport through New Zealand agricultural watersheds - A review

In New Zealand, there is substantial potential for microbial contaminants from agricultural fecal sources to be transported into waterways. The flow and transport pathways for fecal contaminants vary at a range of scales and is dependent on chemical, physical and biological attributes of pathways, soils, microorganisms and landscape characteristics. Understanding contaminant transport pathways from catchment to stream can aid water management strategies. It is not practical, however to conduct direct field measurement for all catchments on the fate and transport of fecal pathogens due to constraints on time, personnel, and material resources. To overcome this problem, fecal source tracking can be utilised to link catchment characteristics to fecal signatures identifying critical sources. In this article, we have reviewed approaches to identifying critical sources and pathways for fecal microorganisms from agricultural sources, and make recommendations for the appropriate use of these fecal source tracking (FST) tools.

Trends in bacterial and fungal communities in ant nests observed with Terminal-Restriction Fragment Length Polymorphism (T-RFLP) and Next Generation Sequencing (NGS) techniques-validity and compatibility in ecological studies

Microbes are ubiquitous and often occur in functionally and taxonomically complex communities. Unveiling these community dynamics is one of the main challenges of microbial research. Combining a robust, cost effective and widely used method such as Terminal Restriction Fragment Length Polymorphism (T-RFLP) with a Next Generation Sequencing (NGS) method (Illumina MiSeq), offers a solid alternative for comprehensive assessment of microbial communities. Here, these two methods were combined in a study of complex bacterial and fungal communities in the nest mounds of the ant Formica exsecta, with the aim to assess the degree to which these methods can be used to complement each other. The results show that these methodologies capture similar spatiotemporal variations, as well as corresponding functional and taxonomical detail, of the microbial communities in a challenging medium consisting of soil, decomposing plant litter and an insect inhabitant. Both methods are suitable for the analysis of complex environmental microbial communities, but when combined, they complement each other well and can provide even more robust results. T-RFLP can be trusted to show similar general community patterns as Illumina MiSeq and remains a good option if resources for NGS methods are lacking.

Quantifying the Relative Contributions of Environmental Sources to the Microbial Community in an Urban Stream under Dry and Wet Weather Conditions

Investigating sources of microbial contamination in urban streams, especially when there are no contributions from combined sewer overflows or sewage effluent discharges, can be challenging. The objectives of this study were to identify the sources of microbes in an urban stream and quantify their relative contributions to the microbial community in the stream under dry and wet weather conditions. A microbial source tracking method relying on the 16S rRNA gene was used to investigate the microbial communities in water samples of an urban stream (i.e., from 11 dry and 6 wet weather events), as well as in streambed sediment, soils, street sweepings, sanitary sewage, an upstream lake, and feces of animals and birds collected between 2013 and 2015. The results showed that the Escherichia coli levels in the stream were significantly higher in wet weather flow than in dry weather flow. The upstream lake contributed approximately 93% of the microbes in dry weather flows. Water discharged from storm drain outfalls was the biggest source of microbes in wet weather flows, with a median contribution of approximately 90% in the rising limb and peak flow and about 75% in the declining limb of storms. Furthermore, about 70 to 75% of the microbes in the storm drain outfall water came from materials washed off from the street surfaces in the watershed. Fecal samples did not appear to contribute substantially to the microbes in environmental samples. The results highlight the significance of street surfaces in contributing microbial loads to urban streams under wet weather conditions.IMPORTANCE Identifying the sources of microbial contamination is important for developing best management practices to protect the water quality of urban streams for recreational uses. This study collected a large number of water samples from an urban stream under both dry and wet weather conditions and provided quantitative information on the relative contributions of various environmental compartments to the overall microbial contamination in the stream under the two weather conditions. The watershed in this study represents urban watersheds where no dominant fecal sources are consistently present. The findings highlight the importance of reducing the direct contribution of microbes from street surfaces in the watershed to urban streams under wet weather conditions. The methods and findings from this study are expected to be useful to stormwater managers and regulatory agencies.

Assessing the origin of bacteria in tap water and distribution system in an unchlorinated drinking water system by SourceTracker using microbial community fingerprints

The general consensus is that the abundance of tap water bacteria is greatly influenced by water purification and distribution. Those bacteria that are released from biofilm in the distribution system are especially considered as the major potential risk for drinking water bio-safety. For the first time, this full-scale study has captured and identified the proportional contribution of the source water, treated water, and distribution system in shaping the tap water bacterial community based on their microbial community fingerprints using the Bayesian "SourceTracker" method. The bacterial community profiles and diversity analyses illustrated that the water purification process shaped the community of planktonic and suspended particle-associated bacteria in treated water. The bacterial communities associated with suspended particles, loose deposits, and biofilm were similar to each other, while the community of tap water planktonic bacteria varied across different locations in distribution system. The microbial source tracking results showed that there was not a detectable contribution of source water to bacterial community in the tap water and distribution system. The planktonic bacteria in the treated water was the major contributor to planktonic bacteria in the tap water (17.7-54.1%). The particle-associated bacterial community in the treated water seeded the bacterial community associated with loose deposits (24.9-32.7%) and biofilm (37.8-43.8%) in the distribution system. In return, the loose deposits and biofilm showed a significant influence on tap water planktonic and particle-associated bacteria, which were location dependent and influenced by hydraulic changes. This was revealed by the increased contribution of loose deposits to tap water planktonic bacteria (from 2.5% to 38.0%) and an increased contribution of biofilm to tap water particle-associated bacteria (from 5.9% to 19.7%) caused by possible hydraulic disturbance from proximal to distal regions. Therefore, our findings indicate that the tap water bacteria could possibly be managed by selecting and operating the purification process properly and cleaning the distribution system effectively.

Application of SourceTracker for Accurate Identification of Fecal Pollution in Recreational Freshwater: A Double-Blinded Study

The efficacy of SourceTracker software to attribute contamination from a variety of fecal sources spiked into ambient freshwater samples was investigated. Double-blinded samples spiked with ≤5 different sources (0.025-10% vol/vol) were evaluated against fecal taxon libraries characterized by next-generation amplicon sequencing. Three libraries, including an initial library (17 nonlocal sources), a blinded source library (5 local sources), and a composite library (local and nonlocal sources), were used with SourceTracker. SourceTracker's predictions of fecal compositions in samples were made, in part, based on distributions of taxa within abundant genera identified as discriminatory by discriminant analyses but also using a large percentage of low abundance taxa. The initial library showed poor ability to characterize blinded samples, but, using local sources, SourceTracker showed 91% accuracy (31/34) at identifying the presence of source contamination, with two false positives for sewage and one for horse. Furthermore, sink predictions of source contamination were positively correlated (Spearman's ρ ≥ 0.88, P < 0.001) with spiked source volumes. Using the composite library did not significantly affect sink predictions ( P > 0.79) compared to those made using the local sources alone. Results of this study indicate that geographically associated fecal samples are required for SourceTracker to assign host sources accurately.

Characterization by fluorescence of dissolved organic matter in rural drinking water storage tanks in Morocco

Water storage tanks, fed directly from the river through opened channels, are particular systems used for water supply in rural areas in Morocco. The stored water is used as drinking water by the surrounding population without any treatment. UV-visible spectroscopy and fluorescence spectroscopy (excitation-emission matrices and synchronous fluorescence) have been tested as rapid methods to assess the quality of the water stored in the reservoirs as well as along the river feeding them. Synchronous fluorescence spectra (SFS50), collected with a difference of 50 nm between excitation and emission wavelengths, revealed a high tryptophan-like fluorescence, indicative of a pollution induced by untreated domestic and/or farm wastewater. The best correlations were obtained between the total SFS50 fluorescence and dissolved organic carbon (DOC) and biological oxygen demand, showing that the contribution of humic-like fluorescent substances cannot be neglected to rapidly assess reservoir water quality in terms of DOC by fluorescence spectroscopy.

Elucidating Waterborne Pathogen Presence and Aiding Source Apportionment in an Impaired Stream

Fecal indicator bacteria (FIB) are the basis for water quality regulations and are considered proxies for waterborne pathogens when conducting human health risk assessments. The direct detection of pathogens in water and simultaneous identification of the source of fecal contamination are possible with microarrays, circumventing the drawbacks to FIB approaches. A multigene target microarray was used to assess the prevalence of waterborne pathogens in a fecally impaired mixed-use watershed. The results indicate that fecal coliforms have improved substantially in the watershed since its listing as a 303(d) impaired stream in 2002 and are now near United States recreational water criterion standards. However, waterborne pathogens are still prevalent in the watershed, as viruses (bocavirus, hepatitis E and A viruses, norovirus, and enterovirus G), bacteria (Campylobacter spp., Clostridium spp., enterohemorrhagic and enterotoxigenic Escherichia coli, uropathogenic E. coli, Enterococcus faecalis, Helicobacter spp., Salmonella spp., and Vibrio spp.), and eukaryotes (Acanthamoeba spp., Entamoeba histolytica, and Naegleria fowleri) were detected. A comparison of the stream microbial ecology with that of sewage, cattle, and swine fecal samples revealed that human sources of fecal contamination dominate in the watershed. The methodology presented is applicable to a wide range of impaired streams for the identification of human health risk due to waterborne pathogens and for the identification of areas for remediation efforts.IMPORTANCE The direct detection of waterborne pathogens in water overcomes many of the limitations of the fecal indicator paradigm. Furthermore, the identification of the source of fecal impairment aids in identifying areas for remediation efforts. Multitarget gene microarrays are shown to simultaneously identify waterborne pathogens and aid in determining the sources of impairment, enabling further focused investigations. This study shows the use of this methodology in a historically impaired watershed in which total maximum daily load reductions have been successfully implemented to reduce risk. The results suggest that while the fecal indicators have been reduced more than 96% and are nearing recreational water criterion levels, pathogens are still detectable in the watershed. Microbial source tracking results show that additional remediation efforts are needed to reduce the impact of human sewage in the watershed.

Toward Forensic Uses of Microbial Source Tracking

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

A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method

Human fecal pollution of recreational waters remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality research and management. However, there are currently no standardized approaches for field implementation and interpretation of qPCR data. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and a novel Bayesian weighted average approach to establish a human fecal contamination score (HFS) that can be used to prioritize sampling sites for remediation based on measured human waste levels. The HFS was then used to investigate 975 study design scenarios utilizing different combinations of sites with varying sampling intensities (daily to once per week) and number of qPCR replicates per sample (2-14 replicates). Findings demonstrate that site prioritization with HFS is feasible and that both sampling intensity and number of qPCR replicates influence reliability of HFS estimates. The novel data analysis strategy presented here provides a prescribed approach for the implementation and interpretation of human-associated HF183/BacR287 qPCR data with the goal of site prioritization based on human fecal pollution levels. In addition, information is provided for future users to customize study designs for optimal HFS performance.

An 18S rRNA Workflow for Characterizing Protists in Sewage, with a Focus on Zoonotic Trichomonads

Microbial eukaryotes (protists) are important components of terrestrial and aquatic environments, as well as animal and human microbiomes. Their relationships with metazoa range from mutualistic to parasitic and zoonotic (i.e., transmissible between humans and animals). Despite their ecological importance, our knowledge of protists in urban environments lags behind that of bacteria, largely due to a lack of experimentally validated high-throughput protocols that produce accurate estimates of protist diversity while minimizing non-protist DNA representation. We optimized protocols for detecting zoonotic protists in raw sewage samples, with a focus on trichomonad taxa. First, we investigated the utility of two commonly used variable regions of the 18S rRNA marker gene, V4 and V9, by amplifying and Sanger sequencing 23 different eukaryotic species, including 16 protist species such as Cryptosporidium parvum, Giardia intestinalis, Toxoplasma gondii, and species of trichomonad. Next, we optimized wet-lab methods for sample processing and Illumina sequencing of both regions from raw sewage collected from a private apartment building in New York City. Our results show that both regions are effective at identifying several zoonotic protists that may be present in sewage. A combination of small extractions (1 mL volumes) performed on the same day as sample collection, and the incorporation of a vertebrate blocking primer, is ideal to detect protist taxa of interest and combat the effects of metazoan DNA. We expect that the robust, standardized methods presented in our workflow will be applicable to investigations of protists in other environmental samples, and will help facilitate large-scale investigations of protistan diversity.

Variation of Bacterial Communities with Water Quality in an Urban Tropical Catchment

A major challenge for assessment of water quality in tropical environments is the natural occurrence and potential growth of Fecal Indicator Bacteria (FIB). To gain a better understanding of the relationship between measured levels of FIB and the distribution of sewage-associated bacteria, including potential pathogens, in the tropics this study compared the abundance of FIB (Total coliforms and E. coli) and the Bacteroidales (HF183 marker) with bacterial community structure determined by next-generation amplicon sequencing. Water was sampled twice over 6 months from 18 sites within a tropical urban catchment and reservoir, followed by extraction of DNA from microorganisms, and sequencing targeting the V3-V4 region of the 16S rRNA gene. Multivariate statistical analyses indicated that bacterial community composition (BCC) varied between reservoir and catchment, within catchment land-uses, and with E. coli concentration. Beta-regression indicated that the proportion of sequences from sewage-associated taxa (SAT) or pathogen-like sequences (PLS) were predicted most significantly by measured levels of E. coli(log MPN/100 mL) (χ² > 8.7; p < 0.003). In addition, SAT were significantly predicted by log HF183 levels (χ²=13.1; p = 0.0003) while PLS were not. Our study suggests that measurements of E. coli concentration could be useful in predicting samples enriched in sewage-associated and pathogen-like bacteria in tropical environments despite the potential for nonconservative behavior.

Microbial source tracking in impaired watersheds using PhyloChip and machine-learning classification

Sources of fecal indicator bacteria are difficult to identify in watersheds that are impacted by a variety of non-point sources. We developed a molecular source tracking test using the PhyloChip microarray that detects and distinguishes fecal bacteria from humans, birds, ruminants, horses, pigs and dogs with a single test. The multiplexed assay targets 9001 different 25-mer fragments of 16S rRNA genes that are common to the bacterial community of each source type. Both random forests and SourceTracker were tested as discrimination tools, with SourceTracker classification producing superior specificity and sensitivity for all source types. Validation with 12 different mammalian sources in mixtures found 100% correct identification of the dominant source and 84-100% specificity. The test was applied to identify sources of fecal indicator bacteria in the Russian River watershed in California. We found widespread contamination by human sources during the wet season proximal to settlements with antiquated septic infrastructure and during the dry season at beaches during intense recreational activity. The test was more sensitive than common fecal indicator tests that failed to identify potential risks at these sites. Conversely, upstream beaches and numerous creeks with less reliance on onsite wastewater treatment contained no fecal signal from humans or other animals; however these waters did contain high counts of fecal indicator bacteria after rain. Microbial community analysis revealed that increased E. coli and enterococci at these locations did not co-occur with common fecal bacteria, but rather co-varied with copiotrophic bacteria that are common in freshwaters with high nutrient and carbon loading, suggesting runoff likely promoted the growth of environmental strains of E. coli and enterococci. These results indicate that machine-learning classification of PhyloChip microarray data can outperform conventional single marker tests that are used to assess health risks, and is an effective tool for distinguishing numerous fecal and environmental sources of pathogen indicators.

Linking nitrification characteristic and microbial community structures in integrated fixed film activated sludge reactor by high-throughput sequencing

The primary goal of this study is to investigate ammonia removal, abundance of nitrifying bacteria and microbial community structures in a laboratory-scale integrated fixed film activated sludge (IFAS) reactor. The results of Illumina MiSeq sequencing based on 16S rRNA genes showed Proteobacteria and Bacteroidetes were the dominant phyla in both biofilm and suspended sludge samples in the IFAS reactor. The dominant ammonia-oxidizing bacteria (AOB) species was Nitrosomonas and the dominant nitrite-oxidizing bacteria species was Nitrospira. The contribution of biofilm to ammonia removal increased from 4.0 ± 0.9% to 37.0 ± 2% when the temperature decreased from 25 °C to 10 °C. The real-time polymerase chain reaction (PCR) result showed the abundance of AOB in suspended sludge was higher than that in biofilm at the same time. However, nitrification is more dependent on attached growth than on suspended growth in the IFAS reactor at 15 °C and 10 °C and the abundance of AOB in biofilm was also higher than that in suspended sludge. The more robust ammonia removal rate at low temperatures by biofilm contributed to the relatively stable ammonia removal, and biofilm attached on carriers in the IFAS reactor is advantageous for nitrification in low-temperature environment.

Epidemiologic evaluation of multiple alternate microbial water quality monitoring indicators at three California beaches

INTRODUCTION

Advances in molecular methods provide new opportunities for directly measuring pathogens or host-associated markers of fecal pollution instead of relying on fecal indicator bacteria (FIB) alone for beach water quality monitoring. Adoption of new indicators depends on identifying relationships between either the presence or concentration of the indicators and illness among swimmers. Here we present results from three epidemiologic studies in which a broad range of bacterial and viral indicators of fecal contamination were measured simultaneously by either culture or molecular methods along with Enterococcus to assess whether they provide better health risk prediction than current microbial indicators of recreational water quality.

METHODS

We conducted prospective cohort studies at three California beaches -- Avalon Bay (Avalon), Doheny State Beach (Doheny), Surfrider State Beach (Malibu) -- during the summers of 2007, 2008 and 2009. The studies enrolled 10,785 swimmers across the beaches and recorded each swimmer's water exposure. Water and sand samples were collected several times per day at multiple locations at each beach and analyzed for up to 41 target indicators using 67 different methodologies. Interviewers contacted participants by phone 10-14 days later and recorded symptoms of gastrointestinal illness occurring after their beach visit. Regression models were used to evaluate the association between water quality indicators and gastrointestinal illness among swimmers at each beach.

RESULTS

F+ coliphage (measured using EPA Method 1602) exhibited a stronger association with GI illness than did EPA Method 1600 at the two beaches where it was measured, while a molecular method, F+ RNA Coliphage Genotype II, was the only indicator significantly associated with GI illness at Malibu. MRSA, a known pathogen, had the strongest association with GI illness of any microbe measured at Avalon. There were two methods targeting human-associated fecal anaerobic bacteria that were more strongly associated with GI illness than EPA Method 1600, but only at Avalon. No indicator combinations consistently had a higher odds ratio than EPA Method 1600, but one composite indicator, based on the number of pathogens detected at a beach, was significantly associated with gastrointestinal illness at both Avalon and Doheny when freshwater flow was high.

DISCUSSION

While EPA Method1600 performed adequately at two beaches based on its consistency of association with gastrointestinal illness and the precision of its estimated associations, F+ coliphage measured by EPA Method 1602 had a stronger association with GI illness under high risk conditions at the two beaches where it was measured. One indicator, F+ Coliphage Genotype II was the only indicator significantly associated with GI illness at Malibu. Several indicators, particularly those targeting human associated bacteria, exhibited relationships with GI illness that were equal to or greater than that of EPA Method 1600 at Avalon, which has a focused human fecal source. Our results suggest that site-specific conditions at each beach determine which indicator or indicators best predict GI illness.

Rapid Microbiome Changes in Freshly Deposited Cow Feces under Field Conditions

Although development of next generation sequencing (NGS) has substantially improved our understanding of the microbial ecology of animal feces, previous studies have mostly focused on freshly excreted feces. There is still limited understanding of the aging process dynamics of fecal microbiomes in intact cowpats exposed to natural environments. Fresh cowpats were sampled at multiple time points for 57 days under field conditions; half the samples were exposed to sunlight (unshaded) while the other half was protected from sunlight (shaded). The 16SRNA hypervariable region 4 was amplified from each sample and sequenced on an Illumina MiSeq Platform. While Clostridia, Bacteroidia, and Sphingobacteria were dominant classes of bacteria in fresh cowpats, Alphaproteobacteria, Betaproteobacteria, Actinobacteria, and Bacilli were the dominant classes by the end of the study, indicating a general shift from anaerobic to aerobic bacterial populations. This change was most likely influenced by the shift from cattle gut (anaerobic) to pasture ground (aerobic). Reduced moisture in cowpats may also contribute to the community shift since air can penetrate the dryer cowpat more easily. Twelve genera consisting pathogenic bacteria were detected, with Mycobacterium, Bacillus, and Clostridium being the most abundant; their combined abundance accounts for 90% of the total pathogenic genera. Taxonomic richness and diversity increased throughout the study for most samples, which could be due to bacteria regrowth and colonization of bacteria from the environment. In contrast to the high taxonomic diversity, the changes of PICRUSt inferred function profile were minimal for all cowpats throughout the study, which suggest that core functions predicted by PICRUSt may be too conserved to distinguish differences between aerobe and anaerobe. To the best of our knowledge, this is the first study demonstrating that cowpat exposure to air and sunlight can cause drastic microbiome changes soon after deposition in natural environments. Our findings offer important insights for future research characterizing the microbiome of feces collected in natural environments and the impact of cattle fecal contamination on water resources.

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

This manuscript describes a duplex digital PCR assay (EntHF183 dPCR) for simultaneous quantification of Enterococcus spp. and the human fecal-associated HF183 marker. The EntHF183 duplex dPCR (referred as EntHF183 dPCR hereon) assay uses the same primer and probe sequences as its published individual quantitative PCR (qPCR) counterparts. Likewise, the same water filtration and DNA extraction procedures as performed prior to qPCR are followed prior to running dPCR. However, the duplex dPCR assay has several advantages over the qPCR assays. Most important, the dPCR assay eliminates the need for running a standard curve and hence, the associated bias and variability, by direct quantification of its targets. In addition, while duplexing (i.e., simultaneous quantification) Enterococcus and HF183 in qPCR often leads to severe underestimation of the less abundant target in a sample, dPCR provides consistent quantification of both targets, whether quantified individually or simultaneously in the same reaction. The dPCR assay is also able to tolerate PCR inhibitor concentrations that are one to two orders of magnitude higher than those tolerated by qPCR. These advantages make the EntHF183 dPCR assay particularly attractive because it simultaneously provides accurate and repeatable information on both general and human-associated fecal contamination in environmental waters without the need to run two separate qPCR assays. Despite its advantages over qPCR, the upper quantification limit of the dPCR assay with currently available instrumentation is approximately four orders of magnitude lower than that achievable by qPCR. Consequently, dilution is needed for measurement of high concentrations of target organisms such as those typically observed following sewage spills.

Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems

Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment.

Assessment of Genetic Markers for Tracking the Sources of Human Wastewater Associated Escherichia coli in Environmental Waters

In this study, we have evaluated the performance characteristics (host-specificity and -sensitivity) of four human wastewater-associated Escherichia coli (E. coli) genetic markers (H8, H12, H14, and H24) in 10 target (human) and nontarget (cat, cattle, deer, dog, emu, goat, horse, kangaroo, and possum) host groups in Southeast Queensland, Australia. The overall host-sensitivity values of the tested markers in human wastewater samples were 1.0 (all human wastewater samples contained the E. coli genetic markers). The overall host-specificity values of these markers to differentiate between human and animal host groups were 0.94, 0.85, 0.72, and 0.57 for H8, H12, H24, and H14, respectively. Based on the higher host-specificity values, H8 and H12 markers were chosen for a validation environmental study. The prevalence of the H8 and H12 markers was determined among human wastewater E. coli isolates collected from a wastewater treatment plant (WWTP). Among the 97 isolates tested, 44 (45%) and 14 (14%) were positive for the H8 and H12 markers, respectively. A total of 307 E. coli isolates were tested from environmental water samples collected in Brisbane, of which 7% and 20% were also positive for the H8 and H12 markers, respectively. Based on our results, we recommend that these markers could be useful when it is important to identify the source(s) of E. coli (whether they originated from human wastewater or not) in environmental waters.

Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

In this study, host-associated molecular markers and bacterial 16S rRNA gene community analysis using high-throughput sequencing were used to identify the sources of fecal pollution in environmental waters in Brisbane, Australia. A total of 92 fecal and composite wastewater samples were collected from different host groups (cat, cattle, dog, horse, human, and kangaroo), and 18 water samples were collected from six sites (BR1 to BR6) along the Brisbane River in Queensland, Australia. Bacterial communities in the fecal, wastewater, and river water samples were sequenced. Water samples were also tested for the presence of bird-associated (GFD), cattle-associated (CowM3), horse-associated, and human-associated (HF183) molecular markers, to provide multiple lines of evidence regarding the possible presence of fecal pollution associated with specific hosts. Among the 18 water samples tested, 83%, 33%, 17%, and 17% were real-time PCR positive for the GFD, HF183, CowM3, and horse markers, respectively. Among the potential sources of fecal pollution in water samples from the river, DNA sequencing tended to show relatively small contributions from wastewater treatment plants (up to 13% of sequence reads). Contributions from other animal sources were rarely detected and were very small (<3% of sequence reads). Source contributions determined via sequence analysis versus detection of molecular markers showed variable agreement. A lack of relationships among fecal indicator bacteria, host-associated molecular markers, and 16S rRNA gene community analysis data was also observed. Nonetheless, we show that bacterial community and host-associated molecular marker analyses can be combined to identify potential sources of fecal pollution in an urban river. This study is a proof of concept, and based on the results, we recommend using bacterial community analysis (where possible) along with PCR detection or quantification of host-associated molecular markers to provide information on the sources of fecal pollution in waterways.

A novel microbial source tracking microarray for pathogen detection and fecal source identification in environmental systems

Pathogen detection and the identification of fecal contamination sources are challenging in environmental waters. Factors including pathogen diversity and ubiquity of fecal indicator bacteria hamper risk assessment and remediation of contamination sources. A custom microarray targeting pathogens (viruses, bacteria, protozoa), microbial source tracking (MST) markers, and antibiotic resistance genes was tested against DNA obtained from whole genome amplification (WGA) of RNA and DNA from sewage and animal (avian, cattle, poultry, and swine) feces. Perfect and mismatch probes established the specificity of the microarray in sewage, and fluorescence decrease of positive probes over a 1:10 dilution series demonstrated semiquantitative measurement. Pathogens, including norovirus, Campylobacter fetus, Helicobacter pylori, Salmonella enterica, and Giardia lamblia were detected in sewage, as well as MST markers and resistance genes to aminoglycosides, beta-lactams, and tetracycline. Sensitivity (percentage true positives) of MST results in sewage and animal waste samples (21-33%) was lower than specificity (83-90%, percentage of true negatives). Next generation DNA sequencing revealed two dominant bacterial families that were common to all sample types: Ruminococcaceae and Lachnospiraceae. Five dominant phyla and 15 dominant families comprised 97% and 74%, respectively, of sequences from all fecal sources. Phyla and families not represented on the microarray are possible candidates for inclusion in subsequent array designs.

Complementary amplicon-based genomic approaches for the study of fungal communities in humans

Recent studies highlight the importance of intestinal fungal microbiota in the development of human disease. Infants, in particular, are an important population in which to study intestinal microbiomes because microbial community structure and dynamics during this formative window of life have the potential to influence host immunity and metabolism. When compared to bacteria, much less is known about the early development of human fungal communities, owing partly to their lower abundance and the relative lack of established molecular and taxonomic tools for their study. Herein, we describe the development, validation, and use of complementary amplicon-based genomic strategies to characterize infant fungal communities and provide quantitative information about Candida, an important fungal genus with respect to intestinal colonization and human disease. Fungal communities were characterized from 11 infant fecal samples using primers that target the internal transcribed spacer (ITS) 2 locus, a region that provides taxonomic discrimination of medically relevant fungi. Each sample yielded an average of 27,553 fungal sequences and Candida albicans was the most abundant species identified by sequencing and quantitative PCR (qPCR). Low numbers of Candida krusei and Candida parapsilosis sequences were observed in several samples, but their presence was detected by species-specific qPCR in only one sample, highlighting a challenge inherent in the study of low-abundance organisms. Overall, the sequencing results revealed that infant fecal samples had fungal diversity comparable to that of bacterial communities in similar-aged infants, which correlated with the relative abundance of C. albicans. We conclude that targeted sequencing of fungal ITS2 amplicons in conjunction with qPCR analyses of specific fungi provides an informative picture of fungal community structure in the human intestinal tract. Our data suggests that the infant intestine harbors diverse fungal species and is consistent with prior culture-based analyses showing that the predominant fungus in the infant intestine is C. albicans.

Changes in bacterial and eukaryotic communities during sewage decomposition in Mississippi river water

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.

Temporal stability of the microbial community in sewage-polluted seawater exposed to natural sunlight cycles and marine microbiota

Billions of gallons of untreated wastewater enter the coastal ocean each year. Once sewage microorganisms are in the marine environment, they are exposed to environmental stressors, such as sunlight and predation. Previous research has investigated the fate of individual sewage microorganisms in seawater but not the entire sewage microbial community. The present study used next-generation sequencing (NGS) to examine how the microbial community in sewage-impacted seawater changes over 48 h when exposed to natural sunlight cycles and marine microbiota. We compared the results from microcosms composed of unfiltered seawater (containing naturally occurring marine microbiota) and filtered seawater (containing no marine microbiota) to investigate the effect of marine microbiota. We also compared the results from microcosms that were exposed to natural sunlight cycles with those from microcosms kept in the dark to investigate the effect of sunlight. The microbial community composition and the relative abundance of operational taxonomic units (OTUs) changed over 48 h in all microcosms. Exposure to sunlight had a significant effect on both community composition and OTU abundance. The effect of marine microbiota, however, was minimal. The proportion of sewage-derived microorganisms present in the microcosms decreased rapidly within 48 h, and the decrease was the most pronounced in the presence of both sunlight and marine microbiota, where the proportion decreased from 85% to 3% of the total microbial community. The results from this study demonstrate the strong effect that sunlight has on microbial community composition, as measured by NGS, and the importance of considering temporal effects in future applications of NGS to identify microbial pollution sources.

Discovering new indicators of fecal pollution

Fecal pollution indicators are essential to identify and remediate contamination sources and protect public health. Historically, easily cultured facultative anaerobes such as fecal coliforms, Escherichia coli, or enterococci have been used but these indicators generally provide no information as to their source. More recently, molecular methods have targeted fecal anaerobes, which are much more abundant in humans and other mammals, and some strains appear to be associated with particular host sources. Next-generation sequencing and microbiome studies have created an unprecedented inventory of microbial communities associated with fecal sources, allowing reexamination of which taxonomic groups are best suited as informative indicators. The use of new computational methods, such as oligotyping coupled with well-established machine learning approaches, is providing new insights into patterns of host association. In this review we examine the basis for host-specificity and the rationale for using 16S rRNA gene targets for alternative indicators and highlight two taxonomic groups, Bacteroidales and Lachnospiraceae, which are rich in host-specific bacterial organisms. Finally, we discuss considerations for using alternative indicators for water quality assessments with a particular focus on detecting human sewage sources of contamination.

Microbial source tracking in a coastal California watershed reveals canines as controllable sources of fecal contamination

Elevated levels of fecal indicator bacteria (FIB), including Escherichia coli and enterococci, trigger coastal beach advisories and signal public health risks. Solving FIB pollution in suburban coastal watersheds is challenging, as there are many potential sources. The Arroyo Burro watershed in Santa Barbara, CA is an example, with its popular, but chronically FIB-contaminated beach. To address, a microbial source tracking study was performed. Surface waters were sampled over 2 years, FIB were quantified, and DNA was analyzed for host-associated fecal markers. Surf zone FIB were only elevated when the coastal lagoon was discharging. Among the fecal sources into the lagoon, including upstream human sources and coastal birds, canines were the most important. Canine sources included input via upstream creek water, which decreased after creek-side residences were educated about proper pet waste disposal, and direct inputs to the lagoon and surf zone, where dog waste could have been tidally exchanged with the lagoon. Based on this study, canine waste can be an influential, yet controllable, fecal source to suburban coastal beaches.

Performance of human fecal anaerobe-associated PCR-based assays in a multi-laboratory method evaluation study

A number of PCR-based methods for detecting human fecal material in environmental waters have been developed over the past decade, but these methods have rarely received independent comparative testing in large multi-laboratory studies. Here, we evaluated ten of these methods (BacH, BacHum-UCD, Bacteroides thetaiotaomicron (BtH), BsteriF1, gyrB, HF183 endpoint, HF183 SYBR, HF183 Taqman(®), HumM2, and Methanobrevibacter smithii nifH (Mnif)) using 64 blind samples prepared in one laboratory. The blind samples contained either one or two fecal sources from human, wastewater or non-human sources. The assay results were assessed for presence/absence of the human markers and also quantitatively while varying the following: 1) classification of samples that were detected but not quantifiable (DNQ) as positive or negative; 2) reference fecal sample concentration unit of measure (such as culturable indicator bacteria, wet mass, total DNA, etc); and 3) human fecal source type (stool, sewage or septage). Assay performance using presence/absence metrics was found to depend on the classification of DNQ samples. The assays that performed best quantitatively varied based on the fecal concentration unit of measure and laboratory protocol. All methods were consistently more sensitive to human stools compared to sewage or septage in both the presence/absence and quantitative analysis. Overall, HF183 Taqman(®) was found to be the most effective marker of human fecal contamination in this California-based study.

Recommendations following a multi-laboratory comparison of microbial source tracking methods

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.

Bacteroidales terminal restriction fragment length polymorphism (TRFLP) for fecal source differentiation in comparison to and in combination with universal bacteria TRFLP

Terminal restriction fragment length polymorphism (TRFLP) is an attractive community analysis method for microbial source tracking (MST) because it is accessible, relatively inexpensive, and can discern multiple fecal sources simultaneously. A new Bacteroidales TRFLP (Bac-TRFLP) method was developed and its source identification performance was evaluated by itself, in comparison to, and in combination with an existing universal bacterial TRFLP method in two laboratories. Sixty-four blind samples from 12 fecal sources (sewage, septage, human, dog, horse, cow, deer, pig, chicken, goose, pigeon, and gull) were used for evaluation. Bac- and Univ-TRFLP exhibited similarly high overall correct identification (>88% and >89%, respectively), excellent specificity regardless of fecal sources, variable sensitivity depending on the source, and stable performance across two laboratories. Compared to Univ-TRFLP, Bac-TRFLP had better sensitivity and specificity with horse, cow, and pig fecal sources but was not suited for certain avian sources such as goose, gull, and pigeon. Combining the general and more targeted TRFLP methods (Univ&Bac-TRFLP) achieved higher overall correct identification (>92%), higher sensitivity and specificity metrics, and higher reproducibility between laboratories. Our results suggest that the Bac-TRFLP and Univ&Bac-TRFLP methods are promising additions to the MST toolbox and warrant further evaluation and utilization in field MST applications.

Performance of forty-one microbial source tracking methods: a twenty-seven lab evaluation study

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.