The growing problem of antibiotic resistance has prompted the need for new and novel antimicrobial therapies. The bacterial cell division pathway holds great promise for the development of novel broad-spectrum antibiotics as the majority of the proteins are essential for viability. The wealth of information regarding bacterial cell division has come from studies of the model organisms Escherichia coli and Bacillus subtilis. Although much has been elucidated regarding this pathway, the functions of many individual proteins remain unsolved. An important model organism for the investigation of cell division is Streptomyces coelicolor. The mycelial Streptomyces are sporulating, Gram-positive bacteria that grow in long branching networks of filamentous cells much like filamentous fungi. The normally essential process of cell division is dispensable for growth and viability of S. coelicolor. More interestingly, there are two different modes of cell division in this organism, one for vegetative growth and one is utilized for synchronous septation during sporulation. It is still unclear how developmental regulators control this switch, but advancements in fluorescence microscopy have shed some insight into the cell division process by allowing direct visualization of many cellular components and their dynamics. To better understand bacterial cell division and its regulation in S. coelicolor, three additional fluorescent proteins (FPs), including m.RFP, CyPet and YPet, have been established in this work. An m.RFP shuttle vector was constructed and the utility of m.RFP was tested by translationally fusing it to a tip-localizing protein, DiviVA. This work demonstrated that m.RFP is functional and an efficient marker for localized proteins. Also, established in this work is a two-colour fluorescence reporter system, which includes the fluorescent proteins CyPet and YPet that can be used to study co-localization and protein-protein interactions within cells. Future plans are to use co-localization of FP fusions and fluorescence resonance energy transfer (FRET) between CyPet and YPet to investigate the assembly of protein complexes within the cells, such as those involved in cell division. These studies will reveal critical information that is needed for the development of drugs that have novel mechanisms of action. / Thesis / Master of Science (MSc)

Since penicillin was discovered in 1928, antibiotic usage in human and veterinary medicine and prevalence of antibiotic resistant bacteria (ARB), has been increasing. While antibiotics and antibiotic resistance genes (ARGs) naturally occur in soils, increasing abundances of ARGs correlate with increased antibiotic usage in agricultural settings. When livestock are treated with antibiotics, the antibiotic compounds, ARB, and ARGs can enter soil via manure excreted onto pastures or applied to other fields as fertilizer, thereby spreading antimicrobial resistance (AMR) in the environment. In addition to human health implications, increased AMR has negative impacts on ecosystem services such as carbon and nitrogen cycling. While many studies have researched antibiotic persistence in agricultural systems and their impacts on soil microbial communities, there are still significant knowledge gaps around the long-term effects of antibiotic exposure in soils, how those impacts differ among soils, and how elements of AMR may differentially transport through soil. To address these knowledge gaps, our objectives were to 1) examine the impact of multi-year repeated additions of manure from cattle administered antibiotics on soil microbial communities, 2) determine the interactive effects of soil moisture and type on soil microbial communities exposed to antibiotics and manure, and 3) differentiate between vertical transport of AMR in the form of viable ARB or ARGs in extracellular plasmids. Our results demonstrate that soil bacterial community structures were consistently altered by 3-year additions of manure from cattle administered antibiotics compared to soil amended with antibiotic-free manure. Furthermore, ARG abundances were higher in soils with manure additions compared to soil without manure, although this was true regardless of whether the cattle were administered antibiotics, suggesting that manure and antibiotic impacts on soil microbial communities can persist over multi-year of repeated manure applications. Additionally, in microcosms, effects of manure from cattle administered antibiotics on ARG abundances, microbial community structures, respiration, and nitrogen pools in soil were seen across multiple soil types and moisture contents, suggesting environmental conditions can alter how manure and antibiotics impact microbial community structure and nutrient cycling. Finally, ARB flowed readily through saturated soil, but were also detectable in the top 5 cm of soil columns. However, ARGs on extracellular plasmids did not flow through soil columns and were not detected in soil, indicating that extracellular DNA does not persist or transport through the soil to any meaningful degree. Overall, these results indicate a nuanced approach is required to mitigate the environmental spread of AMR. Soil management strategies for addressing the AMR crisis should consider the broader context of manure management, as high ARG abundances can come from application of manure from antibiotic-free cattle, and soil microbial communities in individual environments may have varied responses to manure antibiotic exposure. Furthermore, the transport of AMR through soil is complex and dynamic, as elements of AMR may transport differently through soil and require separate consideration in modeling and management. Future AMR management practices that consider diverse factors that affect persistence and spread of AMR in the environment can help protect livestock productivity and maintain the efficacy of antibiotics to protect human and animal health. / Doctor of Philosophy / Antibiotics are an important tool used to fight infections in humans, pets, and livestock. As antibiotics are used more frequently, the bacteria they target are more likely to develop resistance to the antibiotics, leading to increasing cases of infections that are harder to treat and higher risk. Antibiotic resistance can persist and spread in multiple forms, including the antibiotic compounds themselves, as antibiotic resistant bacteria (ARB), or as the genetic material that encodes for antibiotic resistance genes (ARGs). In agricultural systems, when livestock are treated with antibiotics they can excrete the antibiotics, along with ARB and ARGs, in the manure, which is then applied to land as fertilizer. In addition to the associated health risks, the spread of antibiotic resistance impacts microscopic bacteria and fungi in the soil, which are important for recycling nutrients for plants and maintaining ecosystem health. The overall goal of this dissertation was to gain a better understanding of how manure from cattle given antibiotics impacts these bacteria and fungi when manure is applied to the soil. The specific objectives were to 1) look impacts after long-term (multiple years) of manure addition, 2) examine how bacteria and fungi might respond differently to antibiotics in soils of different type or with different amounts of water, and 3) determine if ARGs that exist as free genetic material outside of living bacteria can be moved through the soil with flowing water in the same way as living bacteria. Results showed that while the composition of bacterial and fungal communities in the soil vary from year to year, adding manure with and without antibiotics had both caused different and consistent changes on the composition of bacterial communities. There were also higher concentrations of ARGs in soil that had manure added, however antibiotics in the manure did not cause ARGs to increase further, suggesting that even antibiotic-free manure can impact the spread of antibiotic resistance. Experimental work also demonstrated that the soil type and water content of soil can alter how bacteria and fungi respond to antibiotics in manure. The composition of bacterial and fungal communities, their activity rates, and the amount of nitrogen – an important plant nutrient with availability that is strongly affected by microbial activity – all differed with soil type and water content. Thus, while antibiotic resistance antibiotic resistance can cause measurable changes in soil across a range of environmental conditions, it is also likely to persist and spread in different ways in different environments. Finally, when water containing elements of AMR was added to soil, ARB were shown to both move through the soil easily and remain near the top of soil. In contrast, ARGs contained on genetic material outside of living cells did not move through the soil and were broken down within a few days, suggesting that antibiotic resistance likely spreads through living bacteria more than genes outside of cells. Overall, this work highlights the complexity of understanding the role of environmental transmission in the antibiotic resistance crisis and demonstrates the need for nuanced management approaches that take specific environments and conditions into account.

As climate change exacerbates water scarcity and alters available water and fertilizer resources, it is vital that take appropriate measures to ensure sustainable treatment of water, wastewater, and other waste streams that are protective of public health and support recovery and reuse of water and nutrients. The overarching theme of this dissertation is the advancement of next-generation DNA sequencing (NGS) and computational tools for achieving these goals. A suite of relevant fecal and environmental opportunistic pathogens are examined using both culture-based and NGS-based methods. Of particular concern to this research was not only the attenuation and inactivation of pathogens, but also ensuring that optimal treatment approaches reduce antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). Key systems that were the focus of this effort included nutrient reuse (wastewater-derived biosolids and cattle-derived manure), water reuse, and drinking water systems disrupted by a major hurricane. A field study was carried out to survey a suite of pathogens from source-to tap in six small drinking water systems in Puerto Rico six months after Hurricane Maria. The study revealed that pathogenic Leptospira DNA was detected in all systems that were reliant on surface water. On the other hand, Salmonella spp. was detected in surface and groundwater sources and some distribution system waters both by culture and PCR. The study provided comparison of molecular-, microscopic-, and culture-based analysis for pathogen detection and highlighted the need for disaster preparedness for small water systems, including back-up power supply and access to chlorination as soon as possible after a natural disaster. A second field-study examined wastewater derived solids across an international transect of wastewater treatment plants in order to gain insight into the range of ARG concentrations encountered. It was found that, while total ARGs did not vary between treatment or continent of origin, clinically-relevant ARGs (i.e., ARGs encoding resistance to important classes of antibiotics used in humans) were significantly higher in solids derived from Asian wastewater treatment plants. Estimated loading rates of ARGs to soil under a scenario of land application were determined, highlighting in all cases that they are orders of magnitude higher than in the aqueous effluent. Livestock manure, derived from control cattle and cattle undergoing typical antibiotic treatment, and corresponding composts were also evaluated as common soil amendments in a separate study. In this study, the amendments were applied to two soil types in a greenhouse setting, in order to compare the resulting carriage of ARGs on a root (radish) versus leafy (lettuce) vegetable. Remarkably, radishes were found to harbor the highest relative abundance of total ARGs enumerated by metagenomics, even higher than corresponding soils or manures. Although the total microbial load will be lower on a harvested vegetable, the results suggest that the vegetable surface environment can differentially favor the survival of ARBs. The role of wastewater and water reuse treatment processes in reducing ARB and ARGs was also investigated at field-scale. Two independent wastewater treatment plants both substantially reduced total ARG relative and absolute abundance through biological treatment and settling according to metagenomic analysis. The subsequent water reuse treatment train of one system produced water for non- potable purposes and found further reduction in ARGs after chlorination, but a five hundred percent increase in the relative abundance of ARGs in the subsequent distribution system. In the second plant, which employed a membrane-free ozone-biologically-activated carbon-granular activated carbon treatment train for indirect potable reuse, there were notable increases in total ARG relative abundance following ozonation and chlorination. However, these numbers attenuated below background aquifer levels before recharge. Culture-based analysis of these systems targeting resistant ESKAPE pathogens (Escherichia coil, Staphylococcus aureus, Klebsiella spp., Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterococcus spp.) indicated similar trends as the metagenomic ARG analysis for both systems, but was challenged by sub-optimal media for wastewater samples and low confirmation rates, limiting statistical analysis. In order to advance the application of NGS, molecular, and associated bioinformatic tools for monitoring pathogens and antibiotic resistance in environmental systems, newly emerging methods and field standards for antibiotic resistance assessment were also evaluated. Hybrid assembly, the assembly for both short and long metagenomic sequencing reads, were assessed with an in silico framework in order to determine which available assemblers produced the most accurate and long contigs. Hybrid assembly was found to produce longer and more accurate assemblies at all coverages by reducing error as compared to short read assembly, though the outputs differed in composition from long read assembly. Where it is possible, it is beneficial to sequence using both long- and short-read NGS technologies and employ hybrid assembly, but further validation is recommended. Genome resolved metagenomics has also emerged as a strategy to recover individual bacterial genomes from the mixed metagenomic samples though this is often not well validated. In order to address this, genomes were assembled from reclaimed water systems and were compared against whole-genome sequences of antibiotic resistant E.coli isolates. Metagenome-derived genomes were found to produce similar profiles in wastewater treatment plant influents. A final theme to this dissertation addresses the need to standardize targets, methodologies, and reporting of antibiotic resistance in the environment. A systematic literature review was conducted on assays for the enumeration of key ARGs across aquatic environments and recommendations are summarized for the production of comparable data. In sum, this dissertation advances knowledge about the occurrence of pathogens, ARB, and ARGs across aquatic and agricultural systems and across several countries. Advances are made in the application of NGS tools for environmental monitoring of antibiotic resistance and other targets and a path forward is recommended for continued improvement as both DNA sequencing technologies and computational methodologies continue to rapidly advance. / Doctor of Philosophy / Understanding bacteria in our engineered systems is critical to ensuring drinking water, recycled water, and manure-derived soil amendments are safe for downstream applications. As novel approaches for assessing bacteria are developed, standardized methods and evaluations much be developed to ensure that sound conclusions are made that can appropriately inform policy and practice for the protection of public health. This dissertation focuses on combining bacterial culture and DNA sequencing methods for the study of pathogens (i.e., disease-causing organisms) and antibiotic resistance (i.e., ability of some bacteria to survive antibiotic treatments) in agricultural manure management, water reuse, and drinking water systems. Additionally, this work sought to advance emergent metagenomic analysis tools, which provides a new and potentially powerful pathogen and antibiotic resistance monitoring approach through direct extraction and sequencing of DNA from environmental samples. Antibiotic resistance is a global health challenge and it has been widely recognized that wastewater and agriculture are key control points. When antibiotics are ingested by people or livestock, they select for resistant bacteria in the gut. Mitigation efforts are needed, particularly at wastewater treatment plants and on farms, to ensure that excreted antibiotics and resistant bacteria do not further propagate and pose a risk. However, additional challenges such as climate change have spurred the need for more efficient use of our water and nutrient resources. In this work I examined how nutrient and water reuse treatment methods affect antibiotic resistant bacteria and antibiotic resistance genes using DNA sequencing as well as culture-based methods. In order to assess agricultural practices, a systems approach was conducted at the greenhouse scale to identify key control points to stem the spread of antibiotic resistance when vegetables are grown in soils amended with cattle-derived manure fertilizers. Along the food production chain, vegetables (i.e., radish and lettuce) were found to harbor higher proportions of bacteria carrying antibiotic resistance genes, although the estimated numbers of these bacteria were lower. Solids from an international transect of wastewater treatment plants (Sweden, Switzerland, USA, India, Hong Kong, Phillippenes) were examined because they are also foten used as soil amendments. DNA sequencing of these solids revealed that total measured antibiotic resistance genes did not vary between treatment or continent of origin. Calculations were made to determine the range of total hypothetical outputs of ARGs if the biosolids are land applied. Wastewater reuse systems were also examined using culture and metagenomic DNA analysis so that living pathogens could be compared alongside the total (dead and alive) antibiotic resistance genes. While standard wastewater and subsequent water reuse treatments were found to reduce the absolute numbers of antibiotic resistance genes and bacteria in a treatment plant producing water for non-potable reuse (i.e., irrigation), increases in culturable resistant pathogens and antibiotic resistance genes were apparent in the distribution system (i.e., in the pipes conveying treated water to the point of use). Similar reductions in antibiotic resistant bacteria and resistance genes were also seen in a plant using more advanced treatment (ozonation paired with biofiltration) to produce water suitable for indirect potable reuse via aquifer recharge, but there were indications that ozone and chlorine can increase the proportion of antibiotic resistant bacteria. Finally, genomes were recovered from the metagenomic sequencing analysis and were compared to sequenced culture isolates to validate the capabilities of metagenomic analysis to re-assemble genomes at the strain level, which is often required for pathogen confirmation. Pathogens were also assessed in disrupted drinking water systems in Puerto Rico after Hurricane Maria. Small scale systems that were disrupted by the storm were sampled to identify if pathogens were measurable six months after the hurricane. This work revealed that genes attributed to pathogenic Leptospira were detected in all surface water reliant systems while Salmonella spp. were detected by culture and DNA methods, but only in the source surface and groundwaters, not in the distribution systems delivering water to from the treatment site to the tap. This research also contributed to the advancement of big data analysis pipelines as well as to the standardization of methods to ensure that data produced across studies are comparable. Hybrid assembly, an emergent method that combines both short and long metagenomic DNA sequences generated by different technologies to more accurately recover genomes, was found to improve reliability and accuracy of algorithms aimed at reassembling DNA fragments. Antibiotic resistance is a global challenge, but without standardized methodologies for environmental monitoring, it will be difficult to compare measurements across countries and treatment processes in order to identify effective mitigation strategies. A critical literature review was conducted on assays for the enumeration of key antibiotic resistance genes across aquatic environments so that comparable data can be generated. This will be critical to tap into the tremendous volumes of antibiotic resistance monitoring data being generated around the globe to help identify trends and inform solutions. Collectively, this dissertation advances knowledge about the occurrence of pathogens, antibiotic resistant bacteria and antibiotic resistance genes across aquatic and agricultural systems while also critically evaluating emerging methods for the detection of antibiotic resistance in the environment.

Antibiotic resistance analysis (ARA) of Enterococci was used to determine sources of fecal contamination in three District of Columbia waterways: Rock Creek, the Anacostia River, and the Potomac River. These three waterways were identified as exceeding water quality standards set for fecal coliform levels and were designated by the District of Columbia to the Environmental Protection Agency's 303 (d) impaired waters list. A library profile of 1,806 enterococcus isolates from known sources was built based on antibiotic resistance patterns from thirty concentrations of nine antibiotics. These sources included human, cattle, chicken, horse, goat, sheep, deer, raccoon, muskrat, goose, seagull, coyote, duck, wild turkey, dog, and cat. Antibiotic profiles were characterized for 24 unknown enterococci isolates on each of 198 samples (38 samples from the Potomac River, 79 samples from the Anacostia River, and 81 samples from Rock Creek) collected periodically from July 2002 through April 2003. Two major storm events were also sampled during this period. These isolate profiles were compared to the known source library using logistic regression. Three dominant sources of fecal pollution were detected in the Potomac River: livestock (30%), human (29%), and wildlife (22%). Three dominant signatures were also detected in Rock Creek: horse (26%), human (26%), and wildlife (24%). Human was the only dominant source detected in the Anacostia River, averaging 43% over the sampling period. The results of this study indicate that human is a substantial contributor to the fecal contamination problems, especially in the Anacostia River, but there are significant agricultural and wildlife contributions as well. Significant and predictable seasonal variations were also detected, indicating the influence of precipitation on source distributions. The results of this study will aid the Metropolitan Washington D.C. Council of Governments in making important management decisions to help improve the water quality in and around the Washington D.C. area. Expanding the limits of ARA was also an integral part of this research. Three new and even controversial analytical techniques were run on the data collected from this project in an attempt to improve confidence and provide direction to the results of this study. The first was a comparison of the more commonly used statistical analysis model discriminate analysis (DA) with logistic regression (LR). No significant difference was found between the output of the two models for the known source libraries, therefore no suggestion could be made in favor of one model over the other. Another analytical test of the data was the introduction of a standard requiring isolates to meet a minimum of 80% similarity to the known source profiles where it was classified. With the 80% cutoff, between 41% and 44% of the isolates could not be classified to any source and were placed in an unknown category. Based on the remaining isolates, source distributions were recalculated and were not statistically different than those calculated with no restriction for isolate similarity for matching. The last major test of the data was the analysis of the library for representativeness via pulled sample cross validation and the exclusion of all duplicate patterns from the known source library. These analyses did not confirm the representativeness of the databases, but results were further analyzed based on the implications these analyses have on library based methods. / Master of Science

Anthropozoonotic diseases, defined as infectious diseases caused by pathogens transmitted from humans to wildlife, pose a significant health threat to wildlife populations. Many of these pathogens are also able to move from wildlife reservoirs to humans, termed zoonotic diseases, creating the possibility for bi-directional transmission between humans and wildlife. Recent studies show that a significant proportion of emerging infectious diseases in humans originate in wildlife reservoirs and that the frequency of emergence is increasing, yet the specific transmission pathways still remain speculative in most cases. Human fecal waste is persistent across human-modified landscapes and has been identified as a potential source of disease exposure for wildlife populations living near humans. As part of a long-term study of banded mongoose (Mungos mungo) that live in close association with humans and human fecal waste I used Escherichia coli and banded mongoose (Mungos mungo) for evaluating exchange of fecal waste-borne microorganisms at the human-wildlife interface. Antibiotic resistance was found in 57.5% ° 10.3% (n=87) of mongoose fecal samples and 37.2% ° 5.9% of isolates (n=253). Multidrug resistance was detected in 13.8% ° 4.2% of isolates (n=253). Mongoose and human fecal waste isolates consistently clustered together in phylogenetic analyses and statistical analysis of genetic variation showed no significant differences (p=0.18) between E. coli from human and mongoose populations. These results suggest that human fecal waste contamination is an important mechanism for the transmission of pathogens to both humans and animals, including the spread of antibiotic resistance in the environment, an emerging global health threat. / Master of Science

The reduced capacity of antibiotics to treat infections is one of the greatest health concerns that society faces. There is substantial evidence that links this reduced capacity with the widespread use of antibiotics in livestock production. Livestock can act as reservoirs of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria, which can pass resistance on in the livestock's manure. It is important to understand the fate of antibiotic resistance genes and resistant bacteria in the environment after land-application of manure-based amendments. The goal of this field-scale study was to identify the effects of soil amendments (inorganic fertilizer, compost, or raw manure) and crop cover (lettuce or radish) on sediment transfer, fecal indicator bacteria (FIB), and release of ARGs in runoff over six storm events. Two FIB (Escherichia coli and enterococci) and two ARGs (sulI and ermB) were quantified in runoff from each of the constructed plots throughout the growing season. FIB and ARGs were recovered from all plots, including control plots indicating a background level within the soil. Additionally, only the effects of variability among individual storms had an impact on the concentration of FIB in runoff. Vegetative cover and storm variability affected sediment release. A trend of higher sul1 and ermB in runoff from compost and raw manure-amended plots for at least 2 months after planting crops was observed. Only one of these ARGs (ermB) is associated with the class of drugs given to the dairy cows used for the manure and compost, indicating inherent carriage of some ARGs independent of the type of antibiotic administered, and such genes can persist in the environment. These results suggest that there is a risk of ARGs being carried into areas downgradient from agricultural plots that have been amended with compost or manure. / MS

Antibiotic resistance is a growing human health threat, making infections more difficult to treat and increasing fatalities from and cost of treatment of associated diseases. The rise of multidrug resistant pathogens threatens a return to the pre-antibiotic era where even the most common infections may be impossible to treat. It is estimated that the majority of global antibiotic use, and use in the U.S., is dedicated towards livestock, where they are used to promote growth, treat, or prevent disease. Given that exposure to antibiotics selects for antibiotic resistant bacteria (ARBs) and can stimulate the horizontal transfer of their associated antibiotic resistance genes (ARGs), it is important to examine livestock operations as a reservoir of resistance. Correspondingly, there is growing interest in identifying how agricultural practices can limit the potential for spread of antibiotic resistance through the "farm to fork continuum," starting with antibiotic use practices, manure management and land application and ending with the spread of ARBs and ARGs present onto edible crops and serving as a route of exposure to consumers. This study focused specifically on the effect of composting on the prevalence of ARBs and ARGs in cattle manure. Three composting trials were performed: small-scale, heat-controlled, and large-scale. The small-scale composting trial compared dairy and beef manures, with or without antibiotic treatment (treated beef cattle received chlortetracycline, sulfamethazine, and tylosin while treated dairy cattle received cephapirin and pirlimycin), subject to either static or turned composting. The heat-controlled composting trial examined only dairy manure, with or without antibiotic treatment, subject to static composting, but using external heat tape applied to the composting tumblers to extend the duration of the thermophilic (>55°C) temperature range. The large-scale composting trial examined dairy manure, with or without antibiotic treatment, subject to static composting at a much larger scale that is more realistic to typical farm practices. Samples were analyzed to assess phenotypic resistance using the Kirby Bauer disk diffusion method and by diluting and plating onto antibiotic-supplemented agar. Genetic markers of resistance were also assessed using quantitative polymerase chain reaction (qPCR) to quantify sul1 and tet(W) ARGs; metagenomic DNA sequencing and analysis were also performed to assess and compare total ARG abundance and types across all samples. Results indicate that composting can enrich indicators of phenotypic and genetic resistance traits to certain antibiotics, but that most ARGs are successfully attenuated during composting, as evidenced by the metagenomic sequencing. Maintaining thermophilic composting temperatures for adequate time is necessary for the effective elimination of enteric bacteria. This study suggests that indicator bacteria that survive composting tend to be more resistant than those in the original raw manure; however, extending the thermophilic stage of composting, as was done in the heat-controlled trial, can reduce target indicator bacteria below detection limits. Of the two ARGs specifically quantified via qPCR, prior administration of antibiotics to cattle only had a significant impact on tet(W). There was not an obvious difference in the final antibiotic resistance profiles in the finished beef versus dairy manure composts according to metagenomics analysis. Based on these results, composting is promising as a method of attenuating ARGs, but further research is necessary to examine in depth all of the complex interactions that occur during the composting process to maximize performance. If not applied appropriately, e.g., if time and temperature guidelines are not enforced, then there is potential that composting could exacerbate the spread of certain types of antibiotic resistance. / Master of Science

The reduced efficacy of antibiotics in treating common infections is one of the most pressing health concerns of the 21st Century. Increasing evidence links the widespread use of antibiotics in livestock production to the transfer of bacteria carrying antibiotic resistance genes to the broader environment. It is therefore critical to understand the persistence and dissemination of resistance in agricultural soils to understand potential threats to consumers. The goal of this large-scale agricultural field experiment was to identify the effects of crop (lettuce, radish) and fertilizer type (inorganic, compost, raw manure) on the incidence and persistence of antibiotic-resistant fecal coliforms, a common family of fecal indicator bacteria used to track the environmental spread of antibiotic resistance. Soil samples were collected eight times over a 120-day period and analyzed for fecal coliforms utlizing a suite of MacConkey agars supplemented with different antibiotics (ceftazidime, clindamycin, erythromycin, sulfamethoxazole, and tetracycline). Given the number of samples with resistant fecal coliform concentrations below the limit of detection, analyses to identify the effects of soil treatment and crop relied on Zero-inflated Poisson Regressions. Antibiotic-resistant culturable fecal coliforms were recoverable from soils across all treatments immediately following application, though persistence throughout the experiment varied by antibiotic. Sulfamethoxazole- and tetracycline-resistant fecal coliforms were nondetectable after Day 1; this was expected, as the cattle supplying the manure amendments were not treated with these antibiotics or similar analogs. Clindamycin- and erythromycin-resistant fecal coliforms were nondetectable after 42 days but rebounded on Day 90 in the soil; both of these drugs were of the same antibiotic class as the ones used to treat the dairy cattle during the manure collection period. Ceftazidime-resistant fecal coliform levels were consistently high throughout the duration of the growing season. No statistical differences were observed between root and aboveground crops. Results suggest that soils amended with raw or composted dairy manure are at risk of contamination with antibiotic resistant fecal coliforms; however, composting decreased the antibiotic resistant fecal coliform levels of the macrolide (erythromycin) and lincosamide (clindamycin) antibiotic classes administered to the dairy cattle (cephapirin and pirlimycin). / Master of Science

Antibiotic resistance analysis (ARA) was used to determine sources of fecal pollution in the Blackwater River in South-central Virginia. The Department of Environmental Quality designated six segments as impaired due to high fecal coliform concentrations with non-point source (NPS) agriculture the suspected source of impairment. The Blackwater River watershed encompasses 72,000 ha of dairy, beef, and intensive production agriculture, abundant wildlife populations and many homes with onsite septic systems. A library of antibiotic resistance profiles based on 30 concentrations of 9 antibiotics was developed for 1,451 enterococci isolates from human, cattle, chicken, horse, goat, sheep, deer, raccoon, muskrat, goose, duck, coyote, and wild turkey fecal samples. Each isolate was classified as human, wildlife or livestock. Correct classification rates were 82.3% for human, 86.2% for livestock and 87.4% for wildlife isolates when profiles were analyzed with discriminant analysis. Profiles were also determined for 48 isolates from 128 stream samples collected periodically from August 1999 thru April 2001 and compared to the known sources using discriminate analysis. A human signature was found at each site at least once during the year, ranging from 0.0% to 85.0% of the sample isolates. The livestock signature varied from 2.3% to 100% over sites and months, and the wildlife signature varied from 0.0% to 79.5%. The results indicate that both humans and wildlife contribute to fecal pollution in addition to the suspected source, livestock, and reducing fecal pollution will require consideration of all three sources. The results from this research are being used to develop a total maximum daily load (TMDL) project allocations for fecal coliforms in the Blackwater River. Isolates identified by ARA were also profiled using the Biolog metabolic identification system. A library of metabolic profiles was constructed from known source isolates. Stream isolates were identified by Biolog and the metabolic profile was compared to the Biolog library. Of ten stream isolates identified by ARA as human, the Biolog library identified one as human, four as livestock, and five as wildlife. Of ten isolates identified by ARA as livestock, the Biolog library identified seven as livestock and three as wildlife. Of ten isolates identified by ARA as wildlife, one was identified as human, three as livestock and six as wildlife. The overall correct classification of Blackwater isolates in the Biolog library was 14 of 30 isolates, or 47%. Although the Biolog library was constructed with some isolates from the Blackwater basin, there may not be enough isolates in the Biolog library to adequately represent the variability shown by the Blackwater isolates, resulting in lower than expected correct classifications. In spite of these results, Biolog remains promising as one of several tools with potential as a bacterial source tracking method. / Master of Science

Bacterial evolution has been shaped by the acquisition of clusters of genes called genomic islands through means other than vertical inheritance. These gene clusters provide beneficial traits to the recipient bacteria such as virulence, resistance and the ability to utilize different metabolites, thereby facilitating bacterial adaptation to diverse environments and leading to the emergence of multi-drug resistant pathogens. As identification of genomic islands are of immense biomedical importance, we have developed a novel genomic island detection method, DICEP, to robustly identify genomic islands in bacterial genomes. Once genomic islands were identified, we focused on functional characterization of genes harbored by these islands as an essential step towards understanding their role in providing fitness to the recipient bacterium. We have used a gene co-expression network-based approach to gain insights into the functional association of genes within an island. The network analysis revealed novel pathogenicity associated genes and helped in functional characterization of island genes.