Bacterial contamination due to excessive levels of bacteria is a confounding problem and remediation of impaired watersheds relies on the detection of fecal indicator bacteria and then assessing the source of said bacteria. Bacterial source tracking (BST) is an approach for assessing potential sources of this contamination. The purpose of this study was to utilize both cultivation-independent and –dependent methods to improve the ability to track sources of fecal contamination. First, E. coli community composition was assessed across three standard water quality assessments including USEPA Methods 1603 and 1604, and Colilert®, to determine their impact on BST library-based performance. Results indicate that the three assessed methods of enumeration and isolation may select for different populations of E. coli and standardized methods may be warranted if library-dependent BST is part of a research plan. Next, BST techniques were used to enumerate and characterize E. coli communities across various dairy manure management techniques used in the Leon River watershed in central Texas to determine effectiveness of BST efforts in tracking contamination from dairy manure. Results of this study indicated that manure and effluent management strategies which employed means to remove solids from the manure tended to decrease the levels of E. coli in the effluent. Some E. coli genotypes were found across the managerial treatments even though there were no clear seasonal trends or site groupings among the dataset. The vast majority of the isolates classified using the Texas E. coli BST library were correctly classified back to their major source class, thus increasing confidence in the methods currently being utilized to track dairy fecal contributions in this Central Texas watershed. Finally, deer bacterial fecal communities from south and central Texas were analyzed using 454-pyrosequencing to assess the potential for the development of a deer-specific BST marker. Microbial communities did not cluster by site or year suggesting that deer fecal communities in these Texas regions are stable over time and could be amenable to marker development.

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Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: classification; k-nearest-neighbor (k-n-n); neural networks; linear discriminant analysis (LDA); support vector machines; microbial source tracking (MST); quadratic discriminant analysis (QDA); logistic regression. Includes bibliographical references (p. 59-61).

Swimming in ocean water, including beaches not impacted by known point sources of pollution, continues to pose a rising health concern. Studies which evaluate the relationship between indicator microbes, pathogens, and human health at recreational beaches are rare, especially at non-point beaches, although such studies are necessary for establishing criteria which would protect public health while minimizing economic burdens. The objective of this dissertation was to better understand the non-point source beach system, and hence determine possible directions that should be taken from a beach regulatory perspective in order to protect bather health and minimize economic burdens. This objective was accomplished through two studies. The first study included an initial evaluation of the presence of and associations among indicator microbes, pathogens and environmental conditions at a subtropical, recreational marine beach in South Florida (USA) impacted by non-point sources of pollution. Twelve water and eight sand samples were collected during four sampling events conducted at high or low tide and during elevated or reduced solar insolation conditions. Analyses included fecal indicator bacteria (FIB) (fecal coliform, Escherichia coli, enterococci, Clostridium perfringens), human-associated microbial source tracking (MST) markers (human polyomaviruses [HPyVs] and Enterococcus faecium esp gene), and pathogens (Vibrio vulnificus, Staphylococcus aureus, enterovirus, norovirus, hepatitis A virus, Cryptosporidium spp. and Giardia spp.). The objective of the second study was to capture a series of "snapshots" of the study beach with respect to pathogens and indicator microbe levels, environmental conditions, and cumulative human health effects. Two sets of daily composite samples were collected during the BEACHES epidemiology study conducted in Miami (FL) at the same non-point source subtropical marine beach. These samples were analyzed for several pathogens, microbial source tracking markers, indicator microbes, and environmental parameters similar to those in the first study. Enterococci concentrations in water and sand assessed by qPCR were greater than membrane filtration measurements in both studies. FIB concentrations in water were below recreational water quality standards for three of four sampling events; pathogens and MST markers were also generally undetectable during the first study. FIB levels exceeded regulatory guidelines during one event, accompanied by the detection of HPyVs and pathogens, including the autochthonous bacterium Vibrio vulnificus in both sand and water, the allochthonous protozoan Giardia spp. in water, and Cryptosporidium spp. in sand samples. These elevated microbial levels were detected at high tide, low solar insolation conditions, and after elevated 2 day antecedent rainfall. Analyses of the second study demonstrated that rainfall and tide were also significant factors in determining the presence of both indicator microbes and pathogens. Additional potential associations between environmental factors, microbes and human health effects were also identified. However, more analyses should be conducted as the limited number of samples renders it difficult to make conclusive statements about the relationship between these different factors. The results of this research demonstrate the complexity of beach systems characterized by non-point sources, and how more novel and comprehensive approaches will be needed to assess beach water quality for the purpose of protecting bather health. A recommended approach "The comprehensive tool box with approval process approach" to address the beach complexity is presented and applied to the study beach.

Sources of E. coli were determined from impaired waterways in the Appomattox River watershed (in the lower Piedmont and South-Central Virginia) for the development of bacterial Total Maximum Daily Loads (TMDLs). The Appomattox River watershed is primarily undeveloped with 70.8% of the land forested, 17.0% used for agriculture (mainly livestock production), and 7.7% classified as water, wetland or barren land. The remaining 4.5% is developed for residential, commercial, and industrial land uses (mainly within the city of Petersburg). Using Antibiotic Resistance Analysis, a known source library of 1,280 E. coli isolates (320 isolates per source) was constructed. Water samples were collected monthly for between eleven and fourteen months (11/02-12/03) from 40 locations throughout the Appomattox watershed and analyzed for fecal coliforms, E. coli, and resistance to 7 antibiotics of varying concentrations. A total of 486 water samples (9,907 isolates) were analyzed during the study. The objectives of this study were verify that each sampling site exceeded state bacterial count standards (using fecal coliform data), to compare the Discriminate Analysis and Logistic Regression statistical models for use in the classification of isolates, and finally to determine the source of contamination at each site. The fecal coliform and E.coli data was used to determine if each site exceeded state standards during the assessment period. Thirty-eight of the sites exceeded the fecal coliform standard at least 10% of the time, and thirty-three exceeded the E.coli standard at least 10% of the time. Discriminate Analysis (DA) is typically used to classify isolates, but the results obtained from the DA model were unrealistic based on the watershed land uses. By statistically analyzing the original 1,280 E.coli isolates six different ways, a more appropriate classification of isolates was determined. The six analyzing methods were Regular DA and Logistic Regression (LR); DA and LR where each isolate whose probability fell below 80% was deleted; DA and LR where each isolate whose probability fell below 80% was used to create an Unknown category. The Logistic Regression model with an Unknown category proved to be the most appropriate. By using the Logistic Regression model, with Unknown category, to classify isolates, twenty five of the forty sites were discovered to be contaminated predominately with Livestock and fourteen of the sites predominately by Wildlife. One site was equally divided between these two categories. Human and Pet contamination were not dominant at any of the forty sites. This comparison of the DA and LR statistical methods could change the analysis standard for Bacterial Source Tracking and suggests that the model required to classify isolates depends on the watershed characteristics. / Master of Science

Residents in rural communities across Canada rely on groundwater as their main drinking water source, but the private maintenance of this source may increase the risk of fecal contamination caused by human or animal wastes. Wainfleet, a rural Ontario community, has been under an active boil water advisory for the past decade. The last study to assess groundwater quality, performed in 2007, determined that half of the 586 groundwater wells contained exceedances in total fecal coliform and E. coli counts. A critical examination of fecal contamination levels and its sources is not only necessary for maintaining public health in the township, but is also an opportunity to examine the robustness of culture-independent methods for quantifying and sourcing fecal contamination in groundwater environments across Canada. For this project, culture-based and culture-independent methods were utilized to quantify and source any fecal contaminants in Wainfleet’s groundwater. Culture counts of fecal indicator bacteria (FIB) suggested that some of the groundwater wells were receiving more fecal contamination than others, as expected based on a previous study that was conducted 10 years prior. The groundwater wells with higher E. coli counts also had higher read counts of microbes like Campylobacterales which could come from septic tanks and higher concentrations of oxidized nitrogen which can also indicate human-based fecal contamination. Finally, fecal contamination in groundwater wells with E. coli tested positive for the human Bacteroidales marker. Taken together, this study shows that fecal contamination pervades groundwater wells across the boil water advisory zone, much of which originates from leaking septic tanks and poorly-constructed groundwater wells. In this study, we have shown that a suite of protocols, from physiochemical quantification to targeted sequencing and qPCR, can be used to complement culture-based assays in quantifying and pinpointing fecal contamination in groundwater sources. / Thesis / Master of Science (MSc) / Boil water advisories are enacted when fecal contamination levels exceed provincial limits. Standard methods for quantifying fecal contamination use the culture-based detection of fecal indicator bacteria. Sequencing the 16S rRNA gene and amplifying Bacteroidales markers can also be used to identify novel fecal markers and quantify host-specific contaminants in source waters. Using culture and genetic-based methods determined that groundwater wells across Wainfleet, a Niagara township with the longest active boil water advisory in Canada, contain septic tank microbes and are primarily contaminated by leaking septic tanks. Genetic-based assays can complement culture-based detection of fecal bacteria in groundwater sources across Canada.

The goal of monitoring the water quality of shellfish beds is to provide protection against transmission of water-borne infectious diseases. The Coan River and the Little Wicomico River contain shellfish beds that are closed to harvest due to contamination with fecal bacteria. These two rivers are located in Northumberland County, Virginia, and empty into the lower Potomac River and the Chesapeake Bay. Bacterial source tracking (antibiotic resistance analysis of Eschericia coli) was used to determine the sources of fecal contamination that have caused shellfish harvest closures in these two rivers. A total of 1,248 Eschericia coli isolates were collected from known sources to build a regional library for the rivers. The Virginia Department of Shellfish Sanitation (DSS) and project cooperators collected known source samples from August 2001 to September 2002. The Average Rate of Correct Classification for the known source library was 71.9%, with a total of 930 isolates correctly classified. The categories (and rates of correct classification) were Birds (84.7%), Humans (74.8%), Livestock (72.4%), Pets (62.0%), and Wildlife (65.7%). The library was used to identify the sources of Eschericia coli isolated from DSS sampling stations along the Coan and Little Wicomico Rivers from August 2001 to September 2002. Some stations contained a substantial human signature, while wildlife and birds are also major contributors. The results will be used to decide the necessary changes that need to be addressed if the shellfish harvesting beds are to be reopened. / Master of Science

Water sources are susceptible to faecal contamination from animal and human pollution sources. Pollution of our waterways has significant implications on human health, especially from a pathogen perspective. Microbial source tracking (MST) is a promising field which aims to identify the sources of faecal contamination, and thereby allowing for the development of effective management strategies to minimise pollution and the impact on human health. Many of the currently used methods rely on the identification of host-specific markers within the 16S ribosomal RNA (rRNA) gene of bacteria by use of amplification techniques such as polymerase chain reaction (PCR). However, these methods can be limited by sensitivity, quantification, geographical differences and issues of cost which can limit how many markers are evaluated. Developments in DNA sequencing technologies over the past decade have led to a number of next generation sequencing (NGS) platforms which have a rapid, high throughput approach, resulting in an exponential decrease in the cost of sequencing. This has enabled the development of sequence-based metagenomics, where entire communities from environmental samples can be analysed based on their genetic material. The ability to barcode allows for analysis of multiple samples at once, reducing the cost of sequencing environmental samples even further. This is a promising technique for MST, which has had little investigation to date. The primary focus of the studies described in this thesis was to evaluate the use of NGS technology through a metagenomic approach. Roche 454 amplicon sequencing was used to sequence a 16S rRNA gene target, amplified from faecal and water samples from various sources in New Zealand. Barcode strategies were incorporated in the amplification design to allow multiple samples to be sequenced simultaneously. A proof-of-concept study initially utilised a small sequence dataset to evaluate a range of analysis tools available. Taxonomic identification and diversity measures were used to evaluate a selection of currently available tools designed for analysing metagenomic data, with the Quantitative Insights Into Microbial Ecology (QIIME) platform decided upon for further studies. A larger study, including 35 faecal samples from 13 difference sources and 10 water samples, resulted in 522,065 raw sequencing reads. Diversity results suggest three phyla, Bacteroidetes, Firmicutes and Proteobacteria, are strongly represented across all faecal sources analysed. Microbial diversity analysis using clustering techniques provided evidence of host source being the largest influence on bacterial diversity, with samples from each source generally clustering together. This technique could not be used to identify sources of contamination sources in water samples as the water samples all clustered separately from the faecal samples. More successful was the use of taxonomic classifications to determine bacteria genera that were potentially specific to one source. Water samples were screened for these genera, with six out of the ten water samples being indicators of either ruminant or human contamination. Faecal and water samples were also analysed for a selection of published 16S rRNA PCR markers, using a computational motif-based search method. Of the twenty motifs screened for, 14 were found to be relatively source-specific for ruminant, human, dog or pig faecal samples, with some cross-reactivity with chicken and possum samples. Using this method, the contamination source for six of the ten water samples was identified, with the remaining four samples found to not have enough sequences to assess with confidence. Both metagenomic strategies produced comparable results which were consistent with previous MST analysis. This project demonstrates the potential application of next generation sequencing technologies to microbial source tracking, suggesting the possibility this approach to replace existing microbial source tracking methods.

In Canada, as in many other affluent nations, private well water consumers remain at risk for gastrointestinal (GI) illness due to fecal contamination of groundwater. There have been numerous documented outbreaks of GI illness related to contaminated drinking water. While the general risk to well water consumers has been established, the risk in southern Ontario is poorly understood. As a preliminary step towards understanding this risk, a study of Escherichia coli (E. coli) contamination in private well water was undertaken. Spatial scan statistics were employed to determine the extent of contamination for over 30,000 private wells in southeastern Ontario between 2008 and 2012, inclusive. This analysis revealed one large, temporally stable elevated risk region, and three significant smaller regions within it. The methodology utilized in the primary investigation was then applied to a 2012 dataset for all of southern Ontario, resulting in the identification of three regions of elevated risk. The presence of E. coli, a traditional fecal indicator organism, indicates lack of water potability. To provide knowledge regarding the origins of fecal contamination in southeastern Ontario, a molecular microbial source tracking (MST) study was undertaken. A quantitative real-time Bacteroidales PCR assay specifically targeting human, bovine, and general (specific to 10 hosts) was optimized and applied to 716 private well water samples. Almost half of the samples showed evidence of human fecal contamination, whereas only 13% contained evidence of bovine fecal contamination. Approximately one quarter of well samples tested positive for the general host Bacteroidales assay, with an additional one quarter testing negative for all MST assays. Additionally, spatial scan statistics revealed a region of human-sourced contamination, which geographically corresponded with the E. coli contamination cluster for the same study year. The presence of E. coli contamination clusters among private wells reveals an at-risk group of well water consumers. As such, public health practitioners may use this information to target well stewardship programs in higher risk regions. Humans were the predominant contributors of fecal contamination to private wells within the primary study region. These findings may enable future preventative measures by providing insight into the true origins of groundwater fecal pollution. / Thesis (Master, Pathology & Molecular Medicine) -- Queen's University, 2014-06-02 14:50:16.685

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