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Combining Land Use Information and Small Stream Sampling with PCR-Based Methods for Better Characterization of Diffuse Sources of Human Fecal Pollution Lindsay A. Peed,† Christopher T. Nietch,† Catherine A. Kelty,† Mark Meckes,† Thomas Mooney,‡ Mano Sivaganesan,† and Orin C. Shanks†,* † ‡

U.S. Environmental Protection Agency, Cincinnati, OH University of Cincinnati, Cincinnati, OH

bS Supporting Information ABSTRACT: Diffuse sources of human fecal pollution allow for the direct discharge of waste into receiving waters with minimal or no treatment. Traditional culture-based methods are commonly used to characterize fecal pollution in ambient waters, however these methods do not discern between human and other animal sources of fecal pollution making it difficult to identify diffuse pollution sources. Human-associated quantitative real-time PCR (qPCR) methods in combination with low-order headwatershed sampling, precipitation information, and high-resolution geographic information system land use data can be useful for identifying diffuse source of human fecal pollution in receiving waters. To test this assertion, this study monitored nine headwatersheds over a two-year period potentially impacted by faulty septic systems and leaky sanitary sewer lines. Human fecal pollution was measured using three different human-associated qPCR methods and a positive significant correlation was seen between abundance of humanassociated genetic markers and septic systems following wet weather events. In contrast, a negative correlation was observed with sanitary sewer line densities suggesting septic systems are the predominant diffuse source of human fecal pollution in the study area. These results demonstrate the advantages of combining water sampling, climate information, land-use computer-based modeling, and molecular biology disciplines to better characterize diffuse sources of human fecal pollution in environmental waters.

’ INTRODUCTION Diffuse sources of human fecal pollution can allow for the direct discharge of waste into receiving waters with minimal or no treatment. Unsafe levels of untreated human fecal waste pose a serious health risk when an impacted water source is used for recreation, a drinking reservoir, irrigation, or aquaculture applications.1,2 Human fecal pollution detected in a river, lake or beach often represents the cumulative effect of small amounts of contaminants concentrated from a large drainage area making it extremely difficult to identify the origin(s) of pollution. Diffuse human fecal pollution can originate from a variety of sources such as leaky or damaged sanitary sewer lines, faulty septic systems, illicit waste disposal, and sanitary/combined sewer overflows. As a result, the characterization and management of human fecal pollution is closely linked with local waste management practices, adjacent land use, precipitation, and wet weather hydrology. There are two predominant human waste management practices employed in the majority of industrialized countries including the use of sanitary sewers and septic systems. Sanitary sewers are a type of underground carriage system designed to collect and transport all of the sewage that flows into them to a wastewater treatment facility (WWTF). The United States Environmental r 2011 American Chemical Society

Protection Agency (USEPA) estimates that publicly owned sewer systems account for about 1.24 million miles of sewer pipe in the United States. Much of the United State’s sanitary sewer infrastructure is aging. As a result, collapsed or broken sewer lines are a growing concern in many communities and represent a potential source of diffuse human fecal pollution. Even newer sewer collection systems can suffer from breaks and leaks occurring due to soil settling post construction or erosion under high flooding events for systems built adjacent to a drainage contour. Septic systems are small-scale sewage treatment systems commonly used in rural areas or developing suburbs with no connection to main sewage pipes. A septic system generally consists of one or more tanks connected to an inlet wastewater pipe from a household on one end and a septic drain or leach field at the other. A properly functioning septic system should be odor free and prevent the direct discharge of untreated human waste into the surrounding environment. However, it is common for Received: January 26, 2011 Accepted: May 31, 2011 Revised: May 20, 2011 Published: June 10, 2011 5652

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Environmental Science & Technology septic systems to fail due to age, design, poor operation and maintenance, and/or physical damage due to plant root infiltration. In the United States, approximately 20% of all households are served by septic tank systems.3 In addition, about 37% of new homes built in the U.S. have onsite septic wastewater treatment systems.4 Together, leaky sanitary sewers and faulty septic systems represent two likely sources of diffuse human fecal pollution in many communities in the U.S. and worldwide. The assessment of diffuse fecal pollution in ambient waters is currently dependent on culture-based methods for the detection and enumeration of fecal indicator bacteria (FIB), namely Escherichia coli and enterococci.5 These cultivation approaches require a minimum of 18 h to yield FIB counts, and provide an estimate of the concentration of total fecal pollution from human as well as other animal sources. Alternative methods are now available such as quantitative real-time PCR (qPCR), which allow for the rapid (e4 h) enumeration of general FIB 68 as well as the discrimination of different animal sources.9,10 Several researchers have reported the successful use of both culturebased and qPCR methods to characterize point sources of fecal pollution at WWTF impacted beaches11,12 and freshwater streams.13,14 This same strategy may also prove useful for identifying diffuse sources of fecal pollution in residential areas, especially when combined with local land use data and strategic water sampling locations based on catchment hydrology. Establishing a link between water quality and the adjacent landscape is often constrained by sample site selection, spatial scale of catchment area, availability of associated runoff hydrology, and the accessibility of high-quality land use information. Water quality testing strategies designed to account for these limitations by sampling at a finer spatial scale, use of geographic information system (GIS) technologies, and application of host-associated molecular fecal pollution detection methods may be more successful and provide useful information not available with more traditional approaches. To test this assertion, we conducted sampling in nine streams draining headwatersheds within the East Fork Watershed (EFW) situated in Southwestern Ohio. Together, these headwatersheds represented a continuum of land cover-class percentages and residential human waste management practices. The concentration of fecal pollution was estimated using both cultivation and molecular-based FIB approaches. The origin of diffuse sources of human fecal pollution were identified employing a combination of host-associated qPCR methods, general measurements of water quality, rainfall/runoff indicator data, and land use information. The combination of these different data sources allowed for the characterization of diffuse sources of human fecal pollution in the EFW leading to more efficient, cost-effective, and focused risk management actions.

’ MATERIALS AND METHODS Site Description. The EFW is a 1,295 km2 area situated in

southwest Ohio. Nine headwatersheds were selected for water quality testing including Cemetery Creek (CEC), North Lucy Tributary (NLT), Upper Hall Run (UHL), South Lucy Tributary (SLT), Shaylor Crossing (SHC), Heiserman Stream (HST), South Harsha Tributary (SHA), Owensville Tributary (OWT), and Upper Salt Run (USR) (Figure 1). Headwatersheds ranged in size from 0.41 to 6.9 km2 and varied in land use intensity from densely forested to suburban with residential human waste management practices including septic systems and sanitary sewer lines. Headwatershed boundaries were derived from a

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digital terrain light detection and ranging remote sensing model using the geographic information system (GIS) software ArcGIS (Version 9.3.1; ESRI, Inc.). Headwater sampling sites were strategically located at the headwatershed outlet point where a respective low-order stream intersects the headwatershed boundary (Figure 1). Water Sample Collection and Culture-Based Enumeration of FIB. A total of 215 water samples were collected over a two year study period. Samples were collected in sterile 1 L containers from surface water and were immediately stored on ice during transport to the laboratory. Culture-based enumeration of FIB and water filtration for DNA analysis was performed within six hours of sample collection. FIB including enterococci and E. coli were measured with Enterolert and Colilert IDEXX defined substrate technologies as described by the manufacturer (IDEXX Laboratories, Inc. Westbrook, ME). The single sample maximum allowable density designated by the USEPA Ambient Water Quality Criteria is 235 colonies/100 mL for E. coli and 61 colonies/100 mL for enterococci in fresh water.15 Determination of Wet or Dry Weather Sampling Events. It is well recognized that the relative magnitude and timing of diffuse sources of fecal pollution delivery to receiving streams can be regulated by wet weather conditions.16,17 Once rainfall depth exceeds depression storage the build-up of pollutants during dry weather washes-off as sheet flow or is concentrated in rills, gullies or storm sewers. Therefore, it was desirable to categorize water sampling events as occurring during wet or dry weather flow conditions. The number of sites, associated logistical difficulties of standardizing collection techniques, and the flashy nature of headwaters precluded the use of automatically triggered devices to obtain water samples. Instead, water samples from all sites were collected on the same day within a short period of time ( 0.5). A simple linear regression was performed between estimated log10 copy per 100 mL water and septic system density separately for dry and wet weather events for each qPCR data set. A positive significant correlation was observed between estimated log10 copy per 100 mL water and log10 septic density when there was rainfall wet weather impact (SI Table S1) prior to sampling for all humanassociated qPCR genetic markers including HumM2 (r = þ0.75, p = 0.019, Figure 3), BsteriF1 (r = þ0.74, p = 0.024), and HF183 (r =þ 0.75, p = 0.021) . In contrast, a negative significant correlation was indicated for log10 copy per 100 mL water and sewer line density for human-associated genetic markers HumM2 (r = 0.85, p = 0.004), BsteriF1 (r = 0.70, p = 0.035), and HF183 (r = 0.81, p = 0.009). No significant relationship was observed for any of the general FIB qPCR assays (p > 0.05). Sample Processing Efficiency, Inhibition and Other Quality Controls. Each DNA extract was spiked with a known concentration of salmon sperm DNA to evaluate sample

Figure 3. Scatterplot of log10 septic density and estimated log10 mean copy number per 100 mL for human-associated qPCR assay HumM2. Black and white filled circles indicate data from each headwatershed site collected during dry and wet weather events, respectively. Linear equation represents fitted line for wet weather event data. “r” and “p” values denotes Pearson linear correlation coefficient and significance test statistic, respectively. Blue lines denote the 95% confidence interval for fitted line.

processing efficiency. Only 8.1% (n = 19) of the samples failed the predefined acceptance threshold of Cq 16.8 ( 2.31 (SI Figure S4). Sketa22 mean Cq values for 17 (89.5%) of these samples were within 3 Cq of the acceptance range upperbound (22.1 Cq) and where therefore eligible for Cq adjustment (SI Figure S4). Cq adjustments ranged from 0.11 to 2.93 Cq. Only two sample DNA extracts (0.9%) were removed from the data set because respective Sketa22 mean Cq values exceeded the adjustment ceiling (SI Figure S4). In addition, all DNA extracts were tested for partial or complete amplification inhibition with the CowM2 IAC qPCR assay. IAC detection levels indicated the absence of amplification inhibitors in 97.9% of the samples based on an inhibition threshold of 35.1 ( 1.80 Cq. Sample DNA extracts that failed were discarded from the study (n = 5). No-template, extraction blank, and field blank controls indicated the absence of 5656

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Environmental Science & Technology extraneous DNA molecules in 98.8% of all amplifications (11 false positives of 943 reactions).

’ DISCUSSION Fecal Pollution Trends in East Fork Headwatersheds. Fecal pollution in the EFW headwatersheds is a chronic problem. USEPA recommended cultivation-based methods for enterococci and E. coli indicate unsafe levels of fecal pollution 33100% of the time across all headwatershed sites (Table 1) and that FIB concentrations significantly increase after wet weather events (p < 0.05). This suggests at least two different impact scenarios including (1) a chronic source of fecal contamination that is independent of precipitation or time of sampling, and (2) a wet weather driven impact where pollutants accumulate in catchment areas during antecedent dry periods and are then transported to headwatershed streams via runoff during periods of rainfall. While the culture data confirms the presence of unsafe levels of fecal pollution, it does not identify specific animal sources or associated land use practices making it difficult to plan effective remediation efforts. As a result, it remains unclear whether fecal pollution originates from human waste management systems (sewer lines and/or septic tanks) or other sources such as local wildlife using general FIB culture data alone. As an alternative to general FIB cultivation approaches, hostassociated molecular methods were combined with high-resolution land use information to identify human-associated fecal pollution trends in the watershed. The presence of human fecal pollution was confirmed with three different human-associated qPCR assays and was strongly associated with wet weather suggesting that the primary mechanism of exposure for human fecal pollution is mediated by precipitation. GIS land use characterization quantified the gradient of septic system and sanitary sewer densities across the nine headwatersheds (Figure 1 and Table 2) providing an opportunity to implicate one or both of these practices as sources of human fecal pollution. A positive correlation was observed between all human-associated genetic marker concentrations and septic tank density for samples collected after wet weather (Figure 3) suggesting that septic systems are a significant source. The absence of correlation between general FIB genetic markers and septic density suggests that other factors contribute to the chronic fecal pollution exceedance problems. Host-associated genetic markers for cattle and other ruminants were not detected in any water samples suggesting that the source(s) of fecal contamination are nonruminant in origin. However, birds including ducks and Canada Geese are prevalent waterfowl in the EFW year round due to the availability of water, predator-free grass lands, and a food surplus supplied by humans. Future water quality testing with newly developed goose- and duck-associated genetic markers 9,25 is warranted and may help characterize the problem of chronic fecal pollution in the watershed. For example, if an avian-associated genetic marker was consistently detected regardless of wet weather and time of year, it would suggest that local bird populations play a role in the chronic fecal pollution problem in a particular headwatershed. Advantages of Fine-Scale Land Use Characterization and Low-Order Stream Sampling. The successful identification of septic systems as a key contributor of human fecal pollution in the EFW headwatersheds was not only made possible through the use of human-associated fecal source identification methods, but also due to detailed characterization of land use and a loworder stream sampling strategy. The surrounding landscape can

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have a direct impact on local water quality whether it is the topography dictating the direction and flow of surface runoff, the presence and density of business and residential fecal waste management systems, or simply the amount of forest cover, impervious surfaces, or barren land. The ability to integrate multiple sources of geographic spatial data into a single comprehensive information system can inform decision making regarding public utility management, agricultural practices, urban planning, natural resource management, as well as water quality authorities. Unfortunately, geospatial data such as septic and sewer line information are not always readily available making it more challenging for local water quality managers to utilize this important source of information. Low-order stream sampling also affords several advantages for the identification of diffuse sources of fecal pollution compared to the more common practice of sampling larger water bodies such as rivers, lakes, and beaches. Headwatershed sampling from small streams provide higher resolution information linking water quality to local land use compared to sampling from a larger water body. For example, most rivers are impacted by hundreds to thousands of small streams draining from multiple catchments making it very difficult to associate a particular land use scenario with poor water quality. Shorter in-channel residence time distributions and mixing of adjacent land use diverse drainages are minimized with a low-order stream sampling strategy. In addition, small streams are often surrounded by dense riparian zones, which helps reduce exposure of ambient water to ultraviolet radiation (UV) from sunlight. UV radiation plays a critical role in the die-off of both cultured26,27 and molecular28 indicators of fecal pollution. Any physical habitat variability that results in the reduction of UV exposure would increase the likelihood of detecting indicators of fecal pollution. Finally, small streams are more responsive in terms of volume and flow to recent wet weather events allowing for a more direct connection between potential diffuse sources and water quality measurements. State of the Science: Identification of Diffuse Sources of Human Fecal Pollution. Analysis of EFW samples represents one of the first efforts to integrate host-associated quantitative molecular methods with GIS land use characterization and loworder stream sampling. The application of this interdisciplinary strategy to EFW water samples not only identified failing septic systems as a diffuse source of human fecal pollution, but also suggests several future research activities that will help improve this approach. While there is an increasingly large amount of human-associated fecal source identification methods and performance data available,2932 there is much less known about the existence, density, distribution, and decay of genetic markers associated with other animal sources such as cattle, swine, poultry, and wildlife. The accessibility of reliable host-associated methods for nonhuman animal sources will expand the utility of the reported fecal source identification, GIS land use, small-order stream sampling strategy to other scenarios where potential diffuse fecal pollution problems may arise from agricultural practices or urban runoff. In addition, many human-associated qPCR assays are not 100% specific29 suggesting that more than one assay is needed to identify diffuse sources of human fecal pollution with confidence. Analysis of EFW headwatershed samples with three independent human-associated qPCR assays all indicate that during wet weather sampling events, human fecal pollution is present and that there exists a significant correlation between the concentration of each human-associated genetic marker and density of septic systems and sanitary sewer lines. Additional studies that clearly demonstrate the value of including 5657

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Environmental Science & Technology multiple host-associated methods and combining high resolution land use information with small-order sampling strategies will yield better information for the water quality manager.

’ ASSOCIATED CONTENT

bS

Supporting Information. Nine summary pages numbered S1-S15, four tables, and four figures.This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*Phone: (513) 569-7314; fax: (513) 569-7328; e-mail: shanks.orin@ epa.gov.

’ ACKNOWLEDGMENT We thank the Clermont County Office of Environmental Quality for access to geographic information system septic and sewer data. The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and managed the research described herein. It has been subjected to the Agency’s peer and administrative review and has been approved for external publication. Any opinions expressed in this paper are those of the author (s) and do not necessarily reflect the official positions and policies of the U.S. EPA., Any mention of trade names or commercial products does not constitute endorsement or recommendation for use. ’ REFERENCES (1) Mac Kenzie, W. R.; Hoxie, N. J.; Proctor, M. E.; Gradus, M. S.; Blair, K. A.; Peterson, D. E.; Kazmierczak, J. J.; Addiss, D. G.; Fox, K. R.; Rose, J. B. A massive outbreak in Milwaukee of cryptosporidium infection transmitted through the public water supply. N. Engl. J. Med. 1994, 331 (3), 161–7. (2) Dufour, A. P. Health Effects Criteria for Fresh Recreational Waters, EPA-600/1-84-004; U.S. Environmental Protection Agency: Cincinnati, OH, 1984. (3) Septic systems fact sheet, EPA # 832-F-08-057; U.S. Environmental Protection Agency: Washington, DC, 2008. (4) Lesikar, B. Onsite Wastewater Treatment Systems: Operations and Maintenance; Texas Cooperative Extension: College Station, TX, 2008. (5) Dufour, A. P.; Ballentine, P. Ambient Water Quality Criteria for Bacteria -Bacteriological Ambient Water Quality Criteria for Marine and Fresh Recreational Waters, EPA # 440/5-84-002; Environmental Protection Agency: Washington, DC, 1986. (6) Chern, E. C., Siefring, S., Paar, J., Doolittle, M., Haugland, R. A., Comparison of quantitative PCR assays for Eschrichia coli Targeting Ribosomal RNA and single copy genes. Lett. Appl. Microbiol. 2010. (7) Haugland, R. A.; Siefring, S. C.; Wymer, L. J.; Brenner, K. P.; Dufour, A. P. Comparison of Enterococcus measurements in freshwater at two recreational beaches by quantitative polymerase chain reaction and membrane filter culture analysis. Water Res. 2005, 39 (4), 559–68. (8) Seifring, S. C.; Vama, M.; Atikovic, E.; Wymer, L. J.; Haugland, R. A. Improved real-time PCR assays for the detection of fecal indicator bacteria in surface waters with different instrument and reagent systems. J. Water Health 2008, 6, 225–37. (9) Hamilton, M. J. Y.; Tao, S.; Michael, J. Development of gooseand duck-specific DNA markers to determine sources of Escherichia coli in waterways. Appl. Environ. Microbiol. 2006, 72 (6), 4012–4019. (10) Shanks, O. C.; White, K.; Kelty, C. A.; Hayes, S.; Sivaganesan, M.; Jenkins, M.; Varma, M.; Haugland, R. A. Performance assessment PCR-based assays targeting bacteroidales genetic markers of bovine fecal pollution. Appl. Environ. Microbiol. 2010, 76 (5), 1359–66.

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