Abstract: Antibiotic resistance analysis (ARA), frequency of sampling, and seasonality were evaluated in a rural Virginia watershed dominated by cattle. The selected watershed (Mill Creek) was 3767ha in size, included two small communities (one sewered and one unsewered), and several farms that when combined contained over 3800 beef and dairy cattle. Monthly monitoring of fecal coliforms at two sampling sites in Mill Creek from January to December, 2001, revealed that the recreational standard (1000 colony forming units, CFUs/100ml) was exceeded a total of eight times for a 33% violation rate at each site. In addition, stream samples were collected weekly for 4 consecutive weeks during seasonal high flows (March) and seasonal low flows (September-October), plus daily for 7 consecutive days within the weekly schedules for a combined total of 60 stream samples (30 at each of two sites). The recreational standard was exceeded once during seasonal high flow and nine times during seasonal low flow. Microbial source tracking (MST) was performed by ARA to assess the impact of cattle on water quality within the different sampling routines. The resistance patterns of 2880 water isolates and 1158 known source (host-origin) isolates were determined with seven antibiotics at 28 different concentrations. The 1158 isolate database was reduced to 562 unique isolates when clonal ARA patterns were removed. This database of 562 unique isolates had an average rate of correct classification (ARCC) of 95.4%, and several statistical procedures confirmed the library as accurate and representative. Sixty-five percent of 50 challenge-set isolates from sources, but not samples, used in the library were correctly identified. The 562 unique pattern database was used to classify Escherichia coli isolates from water samples into six host source categories. The ARA results showed that cattle were the major source of pollution in the stream and cattle were the dominant source in over 60% of the water samples. Sampling frequency and seasonality had no effect on the MST results, as cattle dominated both seasons and samplings. Deer were a minor contributor in the summer (high water demand), and geese were a minor contributor in the winter when migratory flocks were observed moving through the watershed. An unexpected human allocation was found, especially under seasonal high flow conditions. The exact origin of this human allocation is not known. This project demonstrated that a host-origin library, based on a phenotypic method, could be developed for a well-defined watershed and was both representative of the sources in the watershed and performed reasonably well against a challenge set.

Abstract: Multiple microbial source-tracking methods were investigated to determine the source of elevated Escherichia coli levels at Bayfront Park Beach in Hamilton Harbour, Lake Ontario. E. coli concentrations were highest in wet foreshore sand (114,000 CFU/g dry sand) and ankle-depth water (177,000CFU/100mL), declining rapidly in deeper waters. Many gull and geese droppings were enumerated each week on the foreshore sand within 2m of the waterline. Both antimicrobial resistance analysis and rep-PCR DNA fingerprinting of E. coli collected at the beach and nearby fecal pollution sources indicated that E. coli in sand and water samples were predominantly from bird droppings rather than from pet droppings or municipal wastewater. Both methods indicated a trend of decreasing bird contamination, and increasing wastewater contamination, moving offshore from the beach. When foreshore sand was treated as a reservoir and secondary source of E. coli, waterborne E. coli were found to be more similar to sand isolates than bird or wastewater isolates out to 150m offshore. Multiple lines of evidence indicated the importance of bird droppings and foreshore sand as primary and secondary sources of E. coli contamination in beach water at Bayfront Park.

Abstract: The ongoing development of microbial source tracking has made it possible to identify contamination sources with varying accuracy, depending on the method used. The purpose of this study was to test the efficiency of the antibiotic resistance analysis (ARA) method under low resistance by tracking the fecal sources at Turkey Creek, Oklahoma exhibiting this condition. The resistance patterns of 772 water-isolates, tested with nine antibiotics, were analyzed by discriminant analysis (DA) utilizing a five-source library containing 2250 isolates. The library passed various representativeness tests; however, two of the pulled-sample tests suggested insufficient sampling. The resubstitution test of the library individual sources showed significant isolate misclassification with an average rate of correct classification (ARCC) of 58%. These misclassifications were explained by low antibiotic resistance (Wilcoxon test P < 0.0001). Seasonal DA of stream E. coli isolates for the pooled sources human/livestock/deer indicated that in fall, the human source dominated (P < 0.0001) at a rate of 56%, and that human and livestock respective contributions in winter (35 and 39%), spring (43 and 40%), and summer (37 and 35%) were similar. Deer scored lower (17-28%) than human and livestock at every season. The DA was revised using results from a misclassification analysis to provide a perspective of the effect caused by low antibiotic resistance and a more realistic determination of the fecal source rates at Turkey Creek. The revision increased livestock rates by 13-14% (0.04 </= P </= 0.06), and decreased human and deer by 6-7%. Negative misclassification into livestock was significant (0.04 </= P </= 0.06). Low antibiotic resistance showed the greatest effect in this category.

Abstract: Watershed management programs often rely on monitoring for a large number of water quality parameters to define contaminant issues. While coliforms have traditionally been used to identify microbial contamination, these indicators cannot discriminate among potential contaminant sources. Microbial source tracking (MST) can provide the missing link that implicates the sources of contamination. The objective of this study was to use a weight-of-evidence approach (land use analysis using GIS, sanitary surveys, traditional water quality monitoring, and MST targets) to identify sources of pollution within a watershed that contains a raw drinking water source. For the study watersheds, statistical analyses demonstrated that one measure each of particulate matter (turbidity, particle counts), organic matter (total organic carbon, dissolved organic carbon, UV(254) absorbance), and indicator organisms (fecal coliforms, enterococci) were adequate for characterizing water quality. While these traditional parameters were useful for assessing overall water quality, they were not intended to differentiate between microbial sources at different locations. In contrast, the MST targets utilized (Rhodococcus coprophilus, sorbitol-fermenting Bifidobacteria, and male-specific coliphages) pinpointed specific sources of microbial pollution. However, these targets could not be used for routine monitoring due to a high percentage of non-detects.

Abstract: In this study, we applied a genome fragment enrichment (GFE) method to select for genomic regions that differ among different fecal metagenomes. Competitive DNA hybridizations were performed between chicken fecal DNA and pig fecal DNA (CP) and between chicken fecal DNA and an avian DNA composite consisting of turkey, goose, and seagull fecal DNA extracts (CB) to enrich for chicken-specific DNA fragments. A total of 471 non-redundant chicken metagenomic sequences were retrieved and analyzed. All of the clone sequences were similar to prokaryotic genes, of which more than 60% could not be assigned to previously characterized functional roles. In general terms, sequences assigned characterized functional roles were associated with cellular processes (11.7%), metabolism (11.0%) and information storage and processing (13.4%). Approximately 53% of the non-redundant sequences are similar to genes present in intestinal bacteria belonging to Clostridia (20.9%), Bacteroidetes (15.0%), and Bacilli (17.3%). Twenty-five sequences from the CP and CB clone libraries were selected to develop chicken fecal-specific PCR assays. These assays were challenged against fecal DNA extracted from 21 different animal species, including mammals and birds. The results from the host-specificity studies showed that 12 of the assays had a high degree of specificity to chicken feces. In addition, three assays were specific to chicken and turkey while another four assays tested positive to more than two avian species, suggesting a broader distribution of some of the enriched gene fragments among different avian fecal microbial communities. Fecal pollution signals were detected using chicken-specific assays in contaminated water samples, although the PCR assays showed different detection limits. These results indicate the need for multiple assays to detect poultry fecal sources of pollution. The competitive DNA hybridization approach used in this study can rapidly select for numerous chicken fecal metagenomic regions that can be used as potential genetic markers for fecal source tracking.

Abstract: Three independent microbial source tracking (MST) methods were applied to a small urban subwatershed in Orange County, California. Fifty-seven water samples collected over summer 2002 were analyzed for human adenovirus and enterovirus. Enterococci and E. coli were isolated for antibiotic resistance analysis (ARA) and for PCR identification of human- and animal-specific toxin genes, respectively. All water samples were PCR negative for human enteroviruses and E. coli human-specific toxin gene. E. coli toxin markers revealed the presence of toxin genes specific to bird, rabbit, and cow. Enterococci ARA results supported this conclusion and indicated that fecal bacteria from bird and wild animal feces as well as soil were the predominant source found in the watershed. An E. coli, isolated from the watershed and inoculated back into the heat-sterilized storm drain water, increased 4 log units within 6 days. Collectively, these results suggest that bird and wild animal feces, soil amendments, and/or fecal coliform growth in the storm drain are the major contributors to the fecal bacterial pollution in downstream areas. However, human adenoviruses were detected on two occasions. Fecal bacterial concentrations were not elevated on these two occasions, suggesting that the elevated levels of fecal indicator bacteria in this small watershed could be unrelated to the source of human adenovirus.

Abstract: Terminal restriction fragment length polymorphism (T-RFLP) analysis is a widespread technique for rapidly fingerprinting microbial communities. Users of T-RFLP frequently overlook the resolving power of well-chosen restriction endonucleases and often fail to report how they chose their enzymes. REPK (Restriction Endonuclease Picker) assists in the rational choice of restriction endonucleases for T-RFLP by finding sets of four restriction endonucleases that together uniquely differentiate user-designated sequence groups. With REPK, users can provide their own sequences (of any gene, not just 16S rRNA), specify the taxonomic rank of interest and choose from a number of filtering options to further narrow down the enzyme selection. Bug tracking is provided, and the source code is open and accessible under the GNU Public License v.2, at http://code.google.com/p/repk. The web server is available without access restrictions at http://rocaplab.ocean.washington.edu/tools/repk.

Abstract: Advances in microbial source tracking (MST) have largely been driven by the need to comply with water quality standards based on traditional indicator bacteria. Recently, a number of culture-independent, and library-independent methods based on polymerase chain reaction (PCR) have been gaining popularity among source trackers. However, only a limited number of these methods have been successfully used in field applications, primarily due to the fact that many of them are still being developed. In this critical outlook, we examine different viewpoints associated with the practical use of MST to identify critical research gaps, propose a priority-based timeline to address them, and outline emerging technologies that will likely impact the future of source tracking. We propose that it is necessary to consider each of these aspects in order to advance towards a unifying framework in source identification, so that fecal pollution monitoring can be reliably used for comprehensive environmental microbial monitoring, to develop risk assessment models, and to implement and validate adequate management practices.

Abstract: The literature on microbial source tracking (MST) suggests that DNA analysis of fecal samples leads to more reliable determinations of bacterial sources of surface water contamination than antibiotic resistance analysis (ARA). Our goal is to determine whether the increased reliability, if any, in library-based MST developed with DNA data is sufficient to justify its higher cost, where the bacteria source predictions are used in TMDL surface water management programs. We describe an application of classification trees for MST applied to ARA and DNA data from samples collected in the Potomac River Watershed in Maryland. Conclusions concerning the comparison of ARA and DNA data, although preliminary at the current time, suggest that the added cost of obtaining DNA data in comparison to the cost of ARA data may not be justified, where MST is applied in TMDL surface water management programs.

Abstract: We report the design and validation of new TaqMan((R)) assays for microbial source tracking based on the amplification of fecal 16S rRNA marker sequences from uncultured cells of the order Bacteroidales. The assays were developed for the detection and enumeration of non-point source input of fecal pollution to watersheds. The quantitative "universal"Bacteroidales assay BacUni-UCD detected all tested stool samples from human volunteers (18 out of 18), cat (7 out of 7), dog (8 out of 8), seagull (10/10), cow (8/8), horse (8/8), and wastewater effluent (14/14). The human assay BacHum-UCD discriminated fully between human and cow stool samples but did not detect all stool samples from human volunteers (12/18). In addition, there was 12.5% detection of dog stool (1/8), but no cross-reactivity with cat, horse, or seagull fecal samples. In contrast, all wastewater samples were positive for the BacHum-UCD marker, supporting its designation as 100% sensitive for mixed-human source identification. The cow-specific assay BacCow-UCD fully discriminated between cow and human stool samples. There was 38% detection of horse stool (3/8), but no cross-specificity with any of the other animal stool samples tested. The dog assay BacCan-UCD discriminated fully between dog and cow stool or seagull guano samples and detected 62.5% stool samples from dogs (5/8). There was some cross-reactivity with 22.2% detection of human stool (4/18), 14.3% detection of cat stool (1/7), and 28.6% detection of wastewater samples (4/14). After validation using stool samples, single-blind tests were used to further demonstrate the efficacy of the developed markers; all assays were sensitive, reproducible, and accurate in the quantification of mixed fecal sources present in aqueous samples. Finally, the new assays were compared with previously published sequences, which showed the new methodologies to be more specific and sensitive. Using Bayes' Theorem, we calculated the conditional probability that the four assays would correctly identify general and host-specific fecal pollution in a specific watershed in California for which 73 water samples had been analyzed. Such an approach allows for a direct comparison of the efficacy of different MST methods, including those based on library-dependent methodologies. For the universal marker BacUni-UCD, the probability that fecal pollution is present when the marker is detected was 1.00; the probability that host-specific pollution is present was 0.98, 0.84, and 0.89 for the human assay HF160F, the cow assay BacCow-UCD, and the dog assay BacCan-UCD, respectively. The application of these markers should provide meaningful information to assist with efforts to identify and control sources of fecal pollution to impaired watersheds.