Fecal Contamination Of Surface Waters Research Articles

Village Settlements in Mountainous Tropical Areas, Hotspots of Fecal Contamination as Evidenced by Escherichia coli and Stanol Concentrations in Stormwater Pulses.

Fecal bacteria in surface water may indicate threats to human health. Our hypothesis is that village settlements in tropical rural areas are major hotspots of fecal contamination because of the number of domestic animals usually roaming in the alleys and the lack of fecal matter treatment before entering the river network. By jointly monitoring the dynamics of Escherichia coli and of seven stanol compounds during four flood events (July-August 2016) at the outlet of a ditch draining sewage and surface runoff out of a village of Northern Lao PDR, our objectives were (1) to assess the range of E. coli concentration in the surface runoff washing off from a village settlement and (2) to identify the major contributory sources of fecal contamination using stanol compounds during flood events. E. coli pulses ranged from 4.7 × 104 to 3.2 × 106 most probable number (MPN) 100 mL-1, with particle-attached E. coli ranging from 83 to 100%. Major contributory feces sources were chickens and humans (about 66 and 29%, respectively), with the highest percentage switching from the human pole to the chicken pole during flood events. Concentrations indicate a severe fecal contamination of surface water during flood events and suggest that villages may be considered as major hotspots of fecal contamination pulses into the river network and thus as point sources in hydrological models.

Land Use, Weather, and Water Quality Factors Associated With Fecal Contamination of Northeastern Streams That Span an Urban-Rural Gradient

Fecal contamination of surface water has been associated with multiple enteric disease outbreaks and food recalls. Thus, it is important to understand factors associated with fecal contamination of agricultural water sources. Since fecal indicator bacteria (FIB) were used to monitor surface water for potential fecal contamination, the purpose of the present study was to characterize associations between environmental factors, and (i) FIB (E. coli, Enterococcus, and coliform) levels, and (ii) host-specific fecal marker detection. This study used data collected from 224 sites along 3 waterways, which spanned an urban-rural gradient around Syracuse, New York. Between 2008 and 2017, 2,816 water samples were collected, and E. coli, Enterococcus, and/or coliform concentrations were enumerated. Thirty-one samples were also tested for human and ruminant microbial source-tracking markers. Water quality (e.g., turbidity, nitrate) and weather data were also collected for each site. Univariable Bayesian regression was used to characterize the relationship between each microbial target and land use, water quality, and weather factor. For each model, probability of direction and region of practical equivalence overlap (ROPE) were calculated to characterize the association's direction and strength, respectively. While levels of different FIB were not correlated with each other, FIB levels were associated with environmental conditions. Specifically, FIB levels were also positively associated with temperature, nutrient and sediment levels. Log10 E. coli levels increased by 0.20 (CI = 0.11, 0.31) and log10 Enterococcus levels increased by 0.68 (CI = 0.08, 1.24) for each log10 increase in salinity and nitrate, respectively. These findings may indicate that similar processes drove microbial, sediment, and nutrient contamination of the sampled watersheds. While fecal contamination was strongly associated with land use, the direction of association varied between FIBs and the buffer distance used to calculate land use metrics. E. coli levels and human marker detection were positively associated with percent pasture cover within 122, 366, and 1,098 m of the sampling site, while Enterococcus and coliform levels were only associated with pasture cover within 1,098 m (not 122 or 366 m). Ruminant markers were positively associated with pasture cover within 122 m, but not 366 or 1,098 m. These findings highlight the importance of considering (i) adjacent land use (and associated non-point sources of contamination) when developing strategies for managing fecal hazards associated in agricultural and recreational water, and (ii) spatial scale (e.g., 122 vs. 1,098 m) when developing these strategies.

EDNA profiling of mammals, birds, and fish of surface waters by mitochondrial metagenomics: application for source tracking of fecal contamination in surface waters.

Knowing the composition of animals present in aquatic ecosystems can tell us about the anthropic pressures on these environments. One of these pressures is the occurrence of fecal contamination. However, this contamination can originate from more than one animal species in areas where urban and agricultural activities overlap. Mitochondrial DNA (mtDNA) has become the standard barcoding tool to identify the presence of animal species in environment. Amplicon-sequencing metagenomics is a powerful approach to derive the animal profile in an environment. However, PCR primers targeting mtDNA of a broad range of animals are highly degenerate or generate short DNA fragments that could cause ambiguous affiliation. Here we report the development of a new set of primers targeting the mitochondrial 16S ribosomal RNA genes of a broad range of terrestrial and aquatic animals, which include mammals, birds, and fishes. These primers successfully amplified mtDNA from environmental DNA (eDNA) extracted from surface waters. Sequencing the resulting amplicons revealed the presence of mammals and birds that may contribute in fecal contamination of surface water. In one of the river samples high in fecal indicator bacteria, human and bovine mtDNA accounted for 40.5% and 4.1% of the sequences, respectively, suggesting fecal contamination by these two animals. These findings indicate that our PCR primers coupled with amplicon-sequencing metagenomics contribute in profiling the animal diversity in the surface waters and its surrounding. This approach could be a valuable tool to identify simultaneously the potential contribution of various animals as sources of fecal contamination in surface waters.

Fecal indicator dynamics at the watershed scale: Variable relationships with land use, season, and water chemistry

Tracking fecal contamination in surface waters is critical to remediating water quality; however, general and source-specific fecal indicators often provide conflicting results. To understand the spatial and temporal dynamics of multiple fecal indicators and the sources they represent, we measured weekly concentrations of two general fecal indicator bacteria (FIB), a genetic indicator of human-associated Bacteroides (HF183), and surface water chemistry in nine mixed land-use watersheds in southwest Virginia, USA. At the watershed scale, general and source-specific indicators were decoupled, with distinct spatial, temporal, and chemical patterns. Random Forest analysis of individual sample variability identified temperature, watershed, nutrients, and cations as top predictors of indicator concentrations. However, these patterns – and the specific nutrients and cations identified – varied by indicator type. Among watersheds, FIB increased with developed land cover and during the summer months, while HF183 increased during the winter and only in urban watersheds. Nutrients generally related poorly to FIB and HF183, except E. coli, which correlated with total nitrogen. In contrast, all fecal indicators showed strong correlations with cations. FIB were more strongly related to calcium, magnesium, and potassium concentrations, while HF183 was related to sodium. These results suggest that, even at the watershed scale, 1) HF183 detects mainly human fecal contamination, while FIB detect broader ecosystem fecal inputs, and 2) poor correlation between specific and generalist fecal indicators is caused by unique spatial, temporal, and transport dynamics of different fecal sources in watersheds.

Evaluación de la Contaminación Microbiológica Presente en los Arroyos La Carolina y La Totora Ubicados en el Partido de Gral. Alvarado. Prov. de Buenos Aires. Argentina.

La contaminación fecal de las aguas superficiales es un problema que incide directamente en la salud humana. El indicador más significativo entre la exposición a aguas ambientales y riesgo de enfermedad es Escherichia coli. El objetivo del trabajo fue evaluar la contaminación ambiental y el riesgo sanitario en los arroyos La Carolina y La Totora, entre julio 2016 y junio 2017, utilizando como indicadores a los Coliformes totales, Coliformes fecales (CF), E. coli y Enterococos fecales (EF). Los análisis se llevaron a cabo siguiendo lo descripto en Standard Methods. Los resultados obtenidos fueron similares en ambos arroyos, se presentaron los mayores recuentos en enero, febrero y marzo del 2017. Si bien, los resultados no presentan valores relevantes, se puede concluir que en casi la totalidad de los muestreos, los resultados de CF, E. coli y EF fueron superiores a los valores guía de la Resolución 42/06 del ADA.

Distribution of Escherichia coli, coliphages and enteric viruses in water, epilithic biofilms and sediments of an urban river in Germany

Fecal contamination of surface water is commonly evaluated by quantification of bacterial or viral indicators such as Escherichia coli and coliphages, or by direct testing for pathogens such as enteric viruses. Retention of fecally derived organisms in biofilms and sediments is less frequently considered. In this study, we assessed the distribution of E. coli, somatic coliphages, and enteric viruses including human adenovirus (HAdV), enterovirus (EV), norovirus genogroup GII (NoV GII) and group A rotavirus (RoV) in an urban river environment in Germany. 24 samples each of water, epilithic biofilms and sediments were examined. E. coli and somatic coliphages were prevalent not only in the flowing water, but also in epilithic biofilms and sediments, where they were accumulated compared to the overlying water. During enhanced rainfall, E. coli and coliphage concentrations increased by approximately 2.5 and 1 log unit, respectively, in the flowing water, whereas concentrations did not change significantly in epilithic biofilms and sediments. The occurrence of human enteric viruses detected by qPCR was higher in water than in biofilms and sediments. 87.5% of all water samples were positive for HAdV. Enteric viruses found less frequently were EV, RoV and NoV GII in 20.8%, 16.7% and 8.3% of the water samples, respectively. In epilithic biofilms and sediments, HAdV was found in 54.2% and 50.0% of the samples, respectively, and EV was found in 4.2% of both biofilm and sediment samples. RoV and NoV GII were not detected in any of the biofilms and sediments. Overall, the prevalence of enteric viruses was in the order of HAdV > EV > RoV ≥ NoV GII. In conclusion, epilithic biofilms and sediments can be reservoirs for fecal indicators and enteric viruses and thus should be taken into consideration when assessing microbial pollution of surface water environments.

Multiple modes of water quality impairment by fecal contamination in a rapidly developing coastal area: southwest Brunswick County, North Carolina.

Fecal contamination of surface waters is a significant problem, particularly in rapidly developing coastal watersheds. Data from a water quality monitoring program in southwest Brunswick County, North Carolina, gathered in support of a regional wastewater and stormwater management program were used to examine likely modes and sources of fecal contamination. Sampling was conducted at 42 locations at 3-4-week intervals between 1996 and 2003, including streams, ponds, and estuarine waters in a variety of land use settings. Expected fecal sources included human wastewater systems (on-site and central), stormwater runoff, and direct deposition by animals. Fecal coliform levels were positively associated with rainfall measures, but frequent high fecal coliform concentrations at times of no rain indicated other modes of contamination as well. Fecal coliform levels were also positively associated with silicate levels, a groundwater source signal, indicating that flux of fecal-contaminated groundwater was a mode of contamination, potentially elevating FC levels in impacted waters independent of stormwater runoff. Fecal contamination by failing septic or sewer systems at many locations was significant and in addition to effects of stormwater runoff. Rainfall was also linked to fecal contamination by central sewage treatment system failures. These results highlight the importance of considering multiple modes of water pollution and different ways in which human activities cause water quality degradation. Management of water quality in coastal regions must therefore recognize diverse drivers of fecal contamination to surface waters.

A farm-scale risk-index for reducing fecal contamination of surface waters.

There is increasing recognition of the adverse impacts of agricultural practices on microbial water quality leading to increased expectation on farmers to manage environmental impacts on water quality. Therefore, farmers require a tool to help them prioritize mitigations targeted at reducing fecal contamination of surface water. A farm-scale risk-index was developed from modeled data on the predicted losses of from selected farm practices. The farm-scale data were then converted to a catchment scale risk value and calibrated against stream concentration data measured in five catchments. The data from the five catchments indicate that there is a relationship between the risk of losses from some farm practices and the resulting levels in the streams. The results show that the adoption of existing mitigation options for fecal contamination should result in a substantial reduction of concentrations in streams flowing through catchments used for intensive dairy farming. However, the relatively high concentrations in the stream when the calculated risk-index values are low indicate that currently available mitigation practices may not be sufficient to achieve contact recreational water quality standards in many catchments due to other sources of . This risk-index approach can be incorporated into existing decision support tools to enable farmers to manage fecal contamination impacts from their farming operations.

Male-specific coliphages for source tracking fecal contamination in surface waters and prevalence of Shiga-toxigenic Escherichia coli in a major produce production region of the Central Coast of California.

To provide data for traditional trace-back studies from fork to farm, it is necessary to determine the environmental sources for Shiga-toxigenic Escherichia coli. We developed SYBR green based reverse-transcriptase PCR methods to determine the prevalence of F+ RNA coliphages (FRNA) as indicators of fecal contamination. Male-specific coliphages, determined using a single-agar overlay method, were prevalent in all surface waters sampled for 8 months. F+ DNA coliphages (FDNA) were predominant compared to FRNA in water samples from majority of sampling locations. Most (90%) of the FRNA were sourced to humans and originated from human-impacted sites. Members of genogroup III represented 77% of FRNA originated from human sources. Furthermore, 93% of FRNA sourced to animals were also detected in water samples from human-impacted sites. Eighty percent of all FRNA were isolated during the winter months indicating seasonality in prevalence. In contrast, FDNA were more prevalent during summer months. E. coli O157:H7 and Shiga-toxigenic E. coli were detected in water samples from locations predominantly influenced by agriculture. Owing to their scarcity, their numbers could not be correlated with the prevalence of FRNA or FDNA in water samples. Both coliform bacteria and generic E. coli from agricultural or human-impacted sites were similar in numbers and thus could not be used to determine the sources of fecal contamination. Data on the prevalence of male-specific coliphages may be invaluable for predicting the sources of fecal contamination and aid in developing methods to prevent enteric pathogen contamination from likely sources during produce production.

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

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

Enterococcus phages as potential tool for identifying sewage inputs in the Great Lakes region

Bacteriophages are viruses living in bacteria that can be used as a tool to detect fecal contamination in surface waters around the world. However, the lack of a universal host strain makes them unsuitable for tracking fecal sources. We evaluated the suitability of two newly isolated Enterococcus host strains (ENT-49 and ENT-55) capable for identifying sewage contamination in impacted waters by targeting phages specific to these hosts. Both host strains were isolated from wastewater samples and identified as E. faecium by 16S rRNA gene sequencing. Occurrence of Enterococcus phages was evaluated in sewage samples (n=15) from five wastewater treatment plants and in fecal samples from twenty-two species of wild and domesticated animals (individual samples; n=22). Levels of Enterococcus phages, F+coliphages, Escherichia coli and enterococci were examined from four rivers, four beaches, and three harbors. Enterococcus phages enumeration was at similar levels (Mean=6.72 Log PFU/100mL) to F+coliphages in all wastewater samples, but were absent from all non-human fecal sources tested. The phages infecting Enterococcus spp. and F+coliphages were not detected in the river samples (detection threshold<10 PFU/100mL), but were present in the beach and harbor samples (range=1.83 to 2.86 Log PFU/100mL). Slightly higher concentrations (range=3.22 to 3.69 Log MPN/100mL) of E. coli and enterococci when compared to F+coliphages and Enterococcus phages, were observed in the river, beach and harbor samples. Our findings suggest that the bacteriophages associated with these particular Enterococcus host strains offer potentially sensitive and human-source specific indicators of enteric pathogen risk.

Canine scent detection and microbial source tracking of human waste contamination in storm drains.

Human fecal contamination of surface waters and drains is difficult to diagnose. DNA-based and chemical analyses of water samples can be used to specifically quantify human waste contamination, but their expense precludes routine use. We evaluated canine scent tracking, using two dogs trained to respond to the scent of municipal wastewater, as a field approach for surveying human fecal contamination. Fecal indicator bacteria, as well as DNA-based and chemical markers of human waste, were analyzed in waters sampled from canine scent-evaluated sites (urban storm drains and creeks). In the field, the dogs responded positively (70% and 100%) at sites for which sampled waters were then confirmed as contaminated with human waste. When both dogs indicated a negative response, human waste markers were absent. Overall, canine scent tracking appears useful for prioritizing sampling sites for which DNA-based and similarly expensive assays can confirm and quantify human waste contamination.

Occurrence and predictive correlations of Escherichia coli and Enterococci at Sandpoint beach (Lake St Clair), Windsor, Ontario and Holiday beach (Lake Erie), Amherstburg, Ontario

Point and nonpoint sources contribute to fecal contamination of surface waters by human pathogens that exist at low concentrations and are difficult, expensive, and/or impossible to easily detect. Therefore, fecal indicator bacteria (FIB) are used as surrogates in identification of fecal contamination, including Escherichia coli (EC) and Enterococcus spp. (ENT), at recreational beaches to protect from adverse health effects from exposure to water-borne pathogens. The objective of the current study was to conduct a preliminary investigation of the environmental processes contributing to the nature and significance of FIB (EC and ENT) over 30 d at Sandpoint beach (Windsor, Ontario) and Holiday beach (Amherstburg, Ontario). Daily, three 100 mL samples were collected for EC and ENT for analysis by Colilert® and Entrolert®, respectively. Additionally, physicochemical and hydrometerological data were measured or taken from data archives. Both EC and ENT populations were dynamic and well correlated to each other (p &amp;lt; 0.05; analysis of variance (ANOVA)) and both FIB correlated with turbidity and wave height (p &amp;lt; 0.10; ANOVA). Despite being geographically close and therefore having similar meteorological data, both beaches exhibited markedly different FIB, turbidity and wave height data, suggesting that beach-specific data should be considered for any future predictive applications.

Evaluation of pepper mild mottle virus, human picobirnavirus and Torque teno virus as indicators of fecal contamination in river water

A reliable indicator is needed to predict and reduce the risk of infection associated with fecal contamination of surface water. Since Pepper mild mottle virus (PMMoV), human picobirnaviruses (hPBV) and Torque teno virus (TTV) have been detected at substantial levels in human feces, we explored whether detection of nucleic acids of these viruses is a suitable indicator of fecal contamination in river water. From September 2008 to December 2009, water samples (n = 111) were collected from the Ruhr and Rhine rivers and from the influents and effluents of a wastewater plant (n = 12). Quantitative real time (RT-) PCR was used to determine the abundance of PMMoV, hPBV, and TTV in comparison to human adenoviruses (HAdV) and human polyomaviruses (HPyV) that are frequently detected in surface water and were previously proposed as indicators. While PMMoV was detected in all river water samples, the other viruses were detected less frequently. The concentration of the studied viruses in positive river water ranged from 5 × 101 to 1.07 × 106 genome equivalents per liter (gen.equ./l). All wastewater samples were positive for PMMoV, HAdV and HPyV, while TTV and hPBV were detected in 6/12 and 3/12 of samples, respectively. To determine if PMMoV is specific to human-derived fecal waste, fecal samples from human (n = 20) and animal (n = 53) were also tested. In contrast to the ubiquity of PMMoV in human feces (19/20) the virus was only detected at low concentration in a minority of the animal fecal samples tested (7/15 from chicken, 1/10 from Geese and 1/6 from cows). Therefore, in this setting TTV and hPBV do not seem to be suitable indicators of fecal contamination in water. Whereas, the high excretion level and dissemination of PMMoV in human sewage and river water suggest that PMMoV could be a promising indicator of fecal pollution in surface water.

Spatial dependency of cholera prevalence on potential cholera reservoirs in an urban area, Kumasi, Ghana

Cholera has been a public health burden in Ghana since the early 1970s. Between 1999 and 2005, a total of 25,636 cases and 620 deaths were officially reported to the WHO. In one of the worst affected urban cities, fecal contamination of surface water is extremely high, and the disease is reported to be prevalent among inhabitants living in close proximity to surface water bodies. Surface runoff from dump sites is a major source of fecal and bacterial contamination of rivers and streams in the study area. This study aims to determine (a) the impacts of surface water contamination on cholera infection and (b) detect and map arbitrary shaped clusters of cholera. A Geographic Information System (GIS) based spatial analysis is used to delineate potential reservoirs of the cholera vibrios; possibly contaminated by surface runoff from open space refuse dumps. Statistical modeling using OLS model reveals a significant negative association between (a) cholera prevalence and proximity to all the potential cholera reservoirs (R2=0.18, p<0.001) and (b) cholera prevalence and proximity to upstream potential cholera reservoirs (R2=0.25, p<0.001). The inclusion of spatial autoregressive coefficients in the OLS model reveals the dependency of the spatial distribution of cholera prevalence on the spatial neighbors of the communities. A flexible scan statistic identifies a most likely cluster with a higher relative risk (RR=2.04, p<0.01) compared with the cluster detected by circular scan statistic (RR=1.60, p<0.01). We conclude that surface water pollution through runoff from waste dump sites play a significant role in cholera infection.

Effects of Agricultural Management, Land Use, and Watershed Scale on E. coli Concentrations in Runoff and Streamflow

Fecal contamination of surface waters is a critical water quality concern with serious human health implications. Many states use Escherichia coli as an indicator organism for fecal contamination and apply watershed models to develop and support bacterial Total Maximum Daily Loads (TMDLs); however, model applicability is greatly restricted due to the sparse availability of E. coli data for validation and calibration at various scales. Similarly, watershed-scale information on the effects of management practices and land use on E. coli fate and transport is limited. Thus, this study was designed to measure E. coli concentrations in edge-of-field runoff and in streams with various agricultural management practices, land uses, and watershed scales. Results showed that application of dairy compost to pasture, cultivated, and mixed land use sites did not significantly affect E. coli concentrations in runoff at the field scale. In contrast, grazed sites had significantly higher runoff E. coli concentrations than cultivated sites, but the increase cannot be attributed solely to grazing cattle. No significant differences in E. coli concentrations were determined for presumably impacted and unimpacted rural streams with differing anthropogenic inputs, which highlights the challenges of managing and regulating bacterial contamination. The results also showed that E. coli concentrations consistently decreased as watershed scale increased from field to small watershed to river basin scale. Results from this study highlight the importance of considering all potential sources (including animal feeding operations, wastewater treatment plants and on-site systems, cultivated and pasture fields, wildlife, and streambed resuspension) to properly assess E. coli contamination in rural watersheds. Results also demonstrated the need for an improved basic scientific understanding of fecal bacteria in the environment to reduce the substantial uncertainty associated with assessing, modeling, managing, and regulating bacterial contamination.

Evaluation of Lactobacillus sobrius/L. amylovorus as a New Microbial Marker of Pig Manure

Based on a comparison of the dominant microbial populations in 17 pig manure samples and using a molecular typing method, we identified a species, Lactobacillus sobrius and Lactobacillus amylovorus (which now are considered a single species and are designated L. sobrius/amylovorus here), that was consistently found in manure. The aim of the present study was to confirm by real-time PCR the relevance of this species as a marker of pig fecal contamination. The specificity of L. sobrius/amylovorus was evaluated in human and animal DNA extracted from feces. The real-time PCR assay then was applied to water samples, including effluents from urban wastewater treatment plants, runoff water, and rivers. L. sobrius/amylovorus was consistently present in all samples of swine origin: 48 fecal samples, 18 from raw manure and 10 from biologically treated manure at mean concentrations of 7.2, 5.9, and 5.0 log(10) cells/g, respectively. The species was not detected in any of the other livestock feces (38 samples from cattle and 16 from sheep), in the 27 human fecal samples, or in the 13 effluent samples from urban wastewater treatment plants. Finally, L. sobrius/amylovorus was not detected in runoff water contaminated by cattle slurry, but it was quantified at concentrations ranging from 3.7 to 6.5 log(10) cells/100 ml in runoff water collected after pig manure was spread on soil. Among the stream water samples in which cultured Escherichia coli was detected, 23% tested positive for L. sobrius/amylovorus. The results of this study indicate that the quantification of L. sobrius/amylovorus using real-time PCR will be useful for identifying pig fecal contamination in surface waters.

Human-specific fecal bacteria in wastewater treatment plant effluents

The objective of this study was to identify fecal bacteria able to persist after wastewater treatment and that could be used as indicators of human fecal contamination. In a first step, the diversity of Bacteroidales, Clostridiaceae, Bifidobacterium, and Bacillus– Streptococcus– Lactobacillus cluster (BSL) was analysed using a fingerprint technique (CE-SSCP) and 16S rDNA libraries in waters collected at the end of the treatment process in different urban wastewater treatment plants. For each group, dominant bacteria present in most effluents were identified. Their origin (human feces, animal feces, non-fecal) was then analysed based on data of their closest relatives in public 16S rDNA databases. Among fecal bacteria recovered in the treated effluents analysed, phylotypes close to Bifidobacterium adolescentis and Bacteroides caccae seem to be specific to human beings. Phylotypes gathering only sequences of human fecal origin were also identified among the BSL and Clostridiaceae, two bacterial groups which have been poorly investigated for bacterial source-tracking purpose. Since these bacteria were detected post-treatment in most wastewater treatment plants, they may constitute potential new indicators of fecal contamination specific to humans that could be used to track fecal contamination of surface water by sewage.

Universal mitochondrial PCR combined with species-specific dot-blot assay as a source-tracking method of human, bovine, chicken, ovine, and porcine in fecal-contaminated surface water

Mitochondrial (mt) DNA has the potential to be used as an animal-specific genetic marker for source-tracking of fecal contamination in surface waters and groundwaters. In this report, we describe the development of a method to detect in a single assay human, bovine, ovine, porcine and chicken mitochondrial (mt) DNA in water. Consensus nucleic sequences were found between human, bovine, porcine, ovine and chicken mtDNA to design three sets of PCR universal primers. Upon polymerase chain reaction (PCR) with a digoxigenin-labeled nucleotide and the universal primers, species determination was carried out by dot-blotting membranes containing specific oligonucleotides for these five animals. Our method was carried out with three river samples and three wastewater samples, and the results were compared with those obtained by multiple nested PCR with specific primers for these five species. Our results showed that the dot-blot assays were as specific and sensitive as the nested-PCR approach. The proposed method has the advantage that it requires the use of only one PCR per sample and very little amounts of DNA. Finally, it is an alternative to multiplex PCR approach which is less sensitive, and shows the way for the development of DNA arrays for source-tracking of many more animal species in fecal-contaminated water.

Considerations When Using Discriminant Function Analysis of Antimicrobial Resistance Profiles To Identify Sources of Fecal Contamination of Surface Water in Michigan

The goals of this study were to (i) identify issues that affect the ability of discriminant function analysis (DA) of antimicrobial resistance profiles to differentiate sources of fecal contamination, (ii) test the accuracy of DA from a known-source library of fecal Escherichia coli isolates with isolates from environmental samples, and (iii) apply this DA to classify E. coli from surface water. A repeated cross-sectional study was used to collect fecal and environmental samples from Michigan livestock, wild geese, and surface water for bacterial isolation, identification, and antimicrobial susceptibility testing using disk diffusion for 12 agents chosen for their importance in treating E. coli infections or for their use as animal feed additives. Nonparametric DA was used to classify E. coli by source species individually and by groups according to antimicrobial exposure. A modified backwards model-building approach was applied to create the best decision rules for isolate differentiation with the smallest number of antimicrobial agents. Decision rules were generated from fecal isolates and applied to environmental isolates to determine the effectiveness of DA for identifying sources of contamination. Principal component analysis was applied to describe differences in resistance patterns between species groups. The average rate of correct classification by DA was improved by reducing the numbers of species classifications and antimicrobial agents. DA was able to correctly classify environmental isolates when fewer than four classifications were used. Water sample isolates were classified by livestock type. An evaluation of the performance of DA must take into consideration relative contributions of random chance and the true discriminatory power of the decision rules.