Widespread antimicrobial resistance, particularly in Gram-negative pathogens, is a serious threat facing the global community. Aminoglycosides are inactivated by enzymes such as aminoglycoside N-acetyltransferase-3 (AAC(3)) and O-nucleotidyltransferase-2” (ANT(2”)), while the New Delhi metallo-b- lactamase-1 (NDM-1) degrades carbapenems. Inhibition of these enzymes should result in bacteria becoming once again susceptible to aminoglycosides and carbapenems. This thesis describes the development of inhibitors to these enzymes, in an effort to rescue the utility of aminoglycoside and carbapenem drug classes through adjuvant therapy. High-throughput screening of protein kinase libraries identified two AAC(3)-Ia inhibitors with a common 3-benzylidene-2-indolinone core. New methods for purification of AAC(3)-Ia and monitoring its activity were developed. A chemical library was built around this scaffold and assessed for SAR. It was found that the initial hit (Z)-methyl 3-(3,5-dibromo-4-hydroxybenzylidene)-2- oxoindoline-5-carboxylate was the most active against AAC(3)-Ia, and alterations to either the 3,5-dibromo-4-hydroxybenzyl warhead or methyl ester substituent resulted in a decrease in activity. Previous whole-cell screening had identified two protein kinase inhibitors with a biphenyl isonicotinamide scaffold as inhibitors of ANT(2”)-Ia. A convergent parallel synthesis was developed, involving Suzuki and amide couplings and protecting group strategies. This methodology was used to assemble a focused chemical library for SAR analysis. Stepwise removal of extraneous complexity from the initial hits yielded a selective ANT(2”)-Ia inhibitor which demonstrated in vivo synergy with gentamicin. Aspergillomarasmine A (AMA) is a natural product with activity against NDM-1. Several derivatives of AMA have been synthesized to assess SAR, but the specific contributions of individual carboxylic acids have yet to determined due to difficulties accessing position 6. A synthetic approach was developed via reductive amination using Garner’s aldehyde as a serine equivalent. This strategy was used to synthesize an AMA analog with a hydroxyl group in place of the carboxylic acid in position 6. Additionally, an imine-promoted isomeric resolution was discovered. / Thesis / Doctor of Philosophy (PhD) / Antibiotics, such as aminoglycosides and carbapenems, are losing their effectiveness against bacteria responsible for deadly diseases. This is often due to resistance enzymes such as aminoglycoside N-acetyltransferase-3 (AAC(3)) and O- nucleotidyltransferase-2” (ANT(2”)), which inactivate aminoglycosides, and the New Delhi metallo-b-lactamase-1 (NDM-1), which destroys carbapenems. If these enzymes are blocked, the antibiotics should work against bacteria again. In order to develop compounds that will inhibit these enzymes, sets of similar compounds are made and tested. Patterns of what chemical groups improve or worsen inhibitory activity are noted and used to make another set of compounds in an iterative process. This thesis describes the development of inhibitors of AAC(3)-Ia and ANT(2”)-Ia by this process. Additionally, a specific compound was made to test if a particular chemical group has a role in inhibiting NDM-1.

Foodborne illnesses caused by Listeria monocytogenes have long been associated with ready-to-eat (RTE) meats contaminated after the primary thermal process has been applied. It is believed that brine solutions used to chill cooked RTE products may serve as a reservoir for L. monocytogenes becoming a potential point of post-processing contamination for RTE meats. Re-circulating ultraviolet light (UV) systems are being used to inactivate L. monocytogenes in chill brines; however very little has been reported on the dose response of healthy and stressed L. monocytogenes to UV in brine solutions. The objectives of this research were to determine 1) minimum dose of UV required to inactivate L. monocytogenes in distilled water, fresh brine, undiluted spent brine, and diluted spent brine, 2) if adaptation to food processing stresses affects the dose response, and 3) if the acquisition of antibiotic resistance mechanisms provides resistance to ultraviolet light 4) effect of stress adaptation on survival in brine solutions. After UV exposure, populations were reduced as follows from greatest to least: water > fresh brine > 5% spent brine > 35% spent brine > 55% spent brine > 100% spent brine (P ≤ 0.05). There were no population differences between acid stressed and antibiotic resistant or healthy and heat shocked (P > 0.05). However, acid-stressed and sulfanilamide-resistant were more resistant to UV light than healthy and heat shocked L. monocytogenes (P ≤ 0.05). Survival in brine solutions (no UV) followed the trend, from greatest to least (P ≤ 0.05): sulfanilamide-resistant > acid-stressed > healthy > heat-shocked. Population estimates decreased from initial inoculation to final sampling for each cell type suspended in spent brine (P ≤ 0.05), but only healthy and heat- shocked cells suspended in fresh brine were significantly reduced (P ≤ 0.05). Knowledge of UV dosing required to control L. monocytogenes in brines used during RTE meat processing, and a greater understanding of the interactions that may influence dose will aid manufacturers in establishing appropriate food safety interventions for these products. / Ph. D.

Antibiotic resistance (AR) is a critical and looming threat to human health that requires action across the One Health continuum (humans, animals, environment). Coordinated surveillance within the environmental sector is largely underdeveloped in current National Action Plans to combat the spread of AR, and a lack of effective study approaches and standard analytical methods have led to a dearth of impactful environmental monitoring data on the prevalence and risk of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in aquatic environments. In this dissertation, integrated surveillance approaches of surface water and wastewater systems are demonstrated, and efforts are made towards standardizing both metagenomic- and culture-based techniques for globally comparable environmental monitoring. A field study of differentially-impacted watersheds on the island of Puerto Rico post-Hurricane Maria demonstrated the effectiveness of metagenomics in defining direct impact of anthropogenic stress and human fecal contamination on the proliferation of ARGs in riverine systems. The contribution of treated wastewater effluents to the dissemination of highly mobile and clinically-relevant ARGs and their connection to local clinical settings was also revealed. At the international scale, a transect of conventional activated sludge wastewater treatment plants (WWTPs), representing both US/European and Asian regions, were found to significantly attenuate ARG abundance through the removal of total bacterial load and human fecal indicators, regardless of influent ARG compositions. Strong structural symmetry between microbiome and ARG compositions through successional treatment stages suggested that horizontal gene transfer plays a relatively minor role in actively shaping resistomes during treatment. Risk assessment models, however, indicated high-priority plasmid-borne ARGs in final treated effluents discharged around the world, indicating potentially increased transmission risks in downstream environments. Advancements were also made toward standardizing methods for the generation of globally representative and comparable metagenomic- and culture-based AR monitoring data via two comprehensive and critical literature reviews. The first review provides guidance in next-generation sequencing (NGS) studies of environmental AR, proposing a framework for experimental controls, adequate sequencing depths, appropriate use of public databases, and the derivation of datatypes that are conducive for risk assessment. The second review focuses on antibiotic-resistant Enterococcus spp. as robust monitoring targets and an attractive alternative to more widely adopted Gram-negative organisms, while proposing workflows that generate universally equivalent datatypes. Finally, quantitative metagenomic (qMeta) techniques were benchmarked using internal reference standards for high-throughput quantification of ARGs with statistical reproducibility. / Doctor of Philosophy / Antimicrobials have contributed to the reduction of infectious diseases in humans and animals since the early 20th century, increasing productivity and saving countless lives. However, their industrial-scale application across human, animal, and agricultural sectors over the last several decades, especially the use of antibiotics, have engendered the proliferation of antibiotic resistance (AR). AR occurs when changes in bacteria cause the drugs used to treat infections to become less effective and has become one of the leading public health threats of the 21st century. The global spread of AR through the transmission and evolution of antibiotic resistant bacteria (ARB; known colloquially as "superbugs") and antibiotic resistance genes (ARGs) across the One Health continuum (i.e., humans, animals, and the environment) is resulting in increased hospitalization, length of hospital stays, suffering, death, and overall health-care associated costs globally. This dissertation demonstrates the use of metagenomics, the sequencing of all genetic material (e.g., DNA) recovered from a microbial community, for the comprehensive monitoring of ARB and ARGs in aquatic environments, a key pathway for the dissemination of AR into and out of human populations. In order to impede the proliferation of AR, surveillance systems are currently in place to track the spread and evolution of ARB and ARGs in humans and livestock, as well as agri-food sectors. However, the surveillance in natural and built environments (i.e., rivers and domestic sewage) has significantly lagged due to the lack of standard monitoring targets and methodologies. It is also a goal of this dissertation to suggest guidance for the collection of metagenomic- and culture-based AR monitoring data to generate universally comparable results that can be included in centralized databases. Riverine systems are ideal models for tracking input of antibiotic resistance to the natural environment by human activity. After Hurricane-Maria, many of Puerto Rico's wastewater treatment plants (WWTPs) went offline, discharging raw sewage to local surface waters. In a cross-sectional study of watersheds impacted by WWTPs, the abundance of ARGs was directly correlated to increases in local population density. Also, highly mobile and clinically-relevant ARGs were found directly downstream of WWTPs across the island. We found that many of these ARGs corresponded well to forms AR endemic to the region. WWTPs are the primary engineering controls put in place to curb the spread of human and animal waste streams and can help to reduce AR. An international transect of conventional activated sludge WWTPs representing US/Europe and Asia were sampled to garner a mechanistic understanding of the fate or ARGs through treatment. Although WWTPs remove total bacteria, human fecal indicators, and much of the abundance of ARGs, mobile and clinically-relevant ARGs are discharged around the world in large quantities. Consideration is needed in certain regions of iv the world where the managing of human waste streams is the first line of defense against the dissemination of resistance to local communities. Two comprehensive critical literature reviews were conducted to evaluate the various methodologies for generating and analyzing metagenomic- and culture-based AR monitoring data. These reviews address the need for experimental rigor and disclosure of extensive metadata for inclusion in future, centralized databases. The articles further provide guidance with respect to universally comparable datatypes and efficient workflows that will aid in the scale-up of the collection of environmental monitoring data within a global surveillance framework. Finally, a study was conducted to benchmark the use of internal DNA reference standards for the absolute quantification of ARGs (i.e., on a ARG copy per volume of sample basis). The statistical framework for ARG detection and its implications for wastewater-based surveillance systems of AR are also discussed.

Antimicrobial resistance (AMR) threatens our modern standard of living with the potential return to a pre-antibiotic condition where deadly infections are no longer treatable. Wastewater treatment plants (WWTPs) are vital components in water sanitation infrastructure and are now also being recognized as valuable monitoring points for antibiotics, antibiotic resistant bacteria (ARB), and antibiotic resistance genes (ARGs) disposed of or excreted by human populations. Hospital waste water is of special interest as a potential focused monitoring point and in general research is needed to establish the benefits of both on-site and community-scale wastewater treatment as important barriers to the disseminators of ARGs into the environment. The research aims described herein examine these components of wastewater treatment and how they relate to AMR indicators identified through metagenomic sequencing. Through monitoring of local WWTPs, it was found that AMR indicators shifted over time and in relation to human behavior that changed due to the COVID-19 pandemic. Hospital wastewater did not measurably impact the microbiome during simulated activated sludge wastewater treatment according to broad-scale metagenomic ARG profiling; however, some clinically-relevant ARGs escaped treatment. Lastly, a study of a transect of WWTPs indicated impacts on the abundance of certain ARGs in downstream riverine receiving environments. Nonetheless, there appeared to be a number of other factors at play, and upstream and downstream resistomes tended to remain similar, calling for further research to delineate impacts of various wastewaters and treatments on ARGs in affected aquatic environments. / Doctor of Philosophy / Antimicrobial resistance (AMR) occurs when bacteria, viruses, and fungi are able to survive in the presence of antibiotics because they carry antibiotic resistance genes (ARGs) encoded in their DNA. AMR is a major public health concern as it makes it so that antibiotics are no longer effective against potentially deadly infections. Wastewater treatment plants (WWTPs) are being discovered as a hub of opportunity for monitoring potential AMR problems in a community. WWTPs receive sewage from homes and various industries. This sewage contains rich information for researchers to examine in terms of which antibiotics, bacteria, and ARGs are circulating in the community. This makes it possible to find out which antibiotics are being consumed in the community and which ARGs might be prevalent. The purpose of this research was to better understand both how WWTPs can be used as monitoring points for AMR and how they can be improved to help reduce ARGs emitted to rivers and streams where treated water is discharged. It was found that the types of ARGs prevalent in wastewater changed over time, especially during the COVID-19 pandemic as people worked from home and changed habits regarding doctors' visits, which impacted antibiotic use. Hospital sewage was studied as a useful indicator of pathogens and ARGs that are challenging a community and also the antibiotics being used. This research explored what happened to ARGs during the treatment of domestic (i.e., from people's homes) wastewater along with hospital wastewater and found that hospital wastewater introduced some ARGs that are typically found in clinical settings, but did not negatively impact the overall wastewater treatment process. Finally, the impact that WWTPs have on rivers to which treated water is discharged was explored. The results indicated that certain ARGs were elevated downstream of the WWTPs. However, when examining all ARGs together, no major shifts due to the treated wastewater were apparent.

Prince William County, located in the rapidly developing Northern Virginia region, contains watersheds of mixed rural and urban/suburban uses. The project goal was to monitor and evaluate 21 stream locations, over 13 months, in the Occoquan Basin identified as impaired due to high E. coli densities. One site on each of eight streams, two sites on each of five streams, and three sites on the remaining stream were chosen for E. coli monitoring and microbial source tracking (MST). MST was performed using antibiotic resistance analysis (ARA) and fluorometric analysis. Escherichia coli was chosen as the indicator bacterium for purposes of comparison with previous project data and because a large body of evidence supports its use in freshwater systems. This study involved the only known MST project to incorporate data from five or more consecutive years. A total of 2854 environmental isolates were collected for analysis with ARA. These isolates were classified using a known source library (KSL) that consisted of 1003 unique resistance patterns. The resistance patterns of the KSL came from known fecal sources (human, pets, livestock, wildlife) in Prince William County. The KSL included isolates from previous years but was also updated with fresh isolates. The accuracy of the KSL was assessed through the use of a challenge set. The challenge set was classified against the KSL using discriminant analysis, verified by logistic regression. The average rate of correct classification was 93% for discriminant analysis and 96% for logistic regression. Results indicated that multiple sources of contamination were present at all sampling locations and that the major source(s) (human, pets, livestock, wildlife) of contamination were generally related to the land-use patterns and human activities at each location. Although no major or minor human signatures were found, all but two locations had either pet or livestock as the major signature, suggesting that human-related activities are playing a key role in contamination of the streams. Pets were the single most frequent major signature and wildlife was the most common minor signature. Fluorometric analysis was used to corroborate human-derived contamination. Fluorometric analysis has the ability to detect the presence of optical brighteners, synthetic compounds added to such household items as laundry detergent, dishwashing detergent and other washing agents. Despite having an undesirably high rate of false negatives (negative fluorometry readings not supported by ARA), fluorometric analysis maintained a low rate of false positives (positive fluorometry readings not supported by ARA) and continued to demonstrate its potential for source tracking. This project represented one of the first attempts at applying a full suite of performance criteria now recommended by the source tracking community for all MST projects. Such concepts as experimental design, toolbox approach, minimum detectable percentage, quantification, accuracy, specificity, robustness, range of applicability, and practicality were successfully incorporated. These performance criteria have in effect set a new standard to which all subsequent MST projects should adhere. / Master of Science

Anthropogenically generated antibiotic resistance genes (ARGs) are considered emerging contaminants, as they are associated with a critical human health challenge, are persist independent of a bacterial host, are subject to transfer between bacteria, and are present at amplified levels in human-impacted environments. Given the gravity of the problem, there is growing interest in advancing water treatment processes capable of limiting ARG dissemination. This study examined the potential for membrane treatment of microconstituent ARGs, and the effect of wastewater colloids on their removal. Native and spiked extracellular vanA (vancomycin resistance) and blaTEM (β-lactam resistance) ARGs were tracked by quantitative polymerase chain reaction through a cascade of membrane filtration steps. To gain insight into potential associations occurring between ARGs and colloidal material, the wastewater colloids were characterized by scanning electron microscopy, as well as in their protein, polysaccharide, and total organic carbon content. The results suggest that extracellular DNA (eDNA) containing ARGs interacts with wastewater colloids, and can both be protected against degradation and be removed more efficiently in the presence of wastewater colloidal material. Thus, ARG removal may be achievable in sustainable water reuse scenarios using lower cost membranes than would have been selected based on molecular size alone. As membranes are likely to play a vital role in water sustainability, the results of this study enable consideration of ARG removal as part of a comprehensive strategy to manage emerging contaminants and to minimize overall public health risks. / Master of Science

The microbial source tracking (MST) methods of antibiotic resistance analysis (ARA) and fluorometry (to detect optical brighteners in detergents) were used in the summers of 2004 and 2005 to determine the origins of fecal pollution at beaches with a past history of, or the potential for, high enterococci counts and posted advisories. At Hilton and Anderson beaches, ARA and fluorometry in the summer of 2004 detected substantial human-origin pollution in locations producing consistently high counts of Enterococcus spp. Investigations by municipal officials led to the fluorometric detection and subsequent repair of sewage infrastructure problems at both beaches. The success of these mitigation efforts was confirmed during the summer of 2005 using ARA and fluorometry, with the results cross-validated by pulsed-field gel electrophoresis (PFGE). Results at other beaches indicated that birds and/or wildlife were largely responsible for elevated enterococci levels during 2004 and 2005. The application of fluorometry proved difficult in opens waters due to high levels of dilution, but showed potential for use in storm drains. An additional study developed and tested a new library-based MST approach based on the pattern of DNA band lengths produced by the amplification of the 16S-23S rDNA intergenic spacer region, and subsequent digestion using the restriction endonuclease MboI. Initial results from small known-source libraries yielded high average rates of correct classification (ARCC). However, an increase in the library size was accompanied by a reduction in the ARCC of the library and the method was deemed unsuccessful, and unsuitable for field application. A final study focused on the potential for classification bias with disproportionate source category sizes using discriminant analysis (DA), logistic regression (LR), and k-nearest neighbor (K-NN) statistical classification algorithms. Findings indicated that DA was the most robust algorithm for use with source category imbalance when measuring both correct and incorrect classification rates. Conversely k-NN was identified as the most sensitive algorithm to imbalances with the greatest levels of distortion obtained from the highest k values. Conclusions of this project include: 1) application of a validation set, as well as a minimum detectable percentage to known-source libraries aids in accurately assessing the classification power of the library and reducing the false positive identification of contributing fecal sources; 2) the validation of MST results using multiple methods is recommended for field applications; 3) fluorometry displayed potential for detecting optical brighteners as indicators of sewage leaks in storm drains; 4) the digestion of the 16S-23S rDNA intergenic spacer region of Enterococcus spp. using MboI does not provided suitable discriminatory power for use as an MST method; and 5) DA was the least, and k-NN the most, sensitive algorithm to imbalances in the size of source categories in a known-source library. / Ph. D.

The treatment of water and wastewater is energy intensive, and there is an urgent need to develop new approaches to address the water-energy challenges. Bioelectrochemical systems (BES) are energy-efficient technologies that can treat wastewater and simultaneously achieve multiple functions such as energy generation, hydrogen production and/or desalination. The objectives of this dissertation are to understand the fundamental microbiology of BES, develop cost-effective cathode catalysts, optimize the process engineering and identify the application niches. It has been shown in Chapter 2 that electrochemically active bacteria can take advantage of shuttle-mediated EET and create optimal anode salinities for their dominance. A novel statistical model has been developed based on the taxonomic data to understand and predict functional dynamics and current production. In Chapter 3, 4 and 5, three cathode catalyst (i.e., N- and S- co-doped porous carbon nanosheets, N-doped bamboo-like CNTs and MoS2 coated on CNTs) have been synthesized and showed effective catalysis of oxygen reduction reaction or hydrogen evolution reaction in BES. Chapter 6, 7 and 8 have demonstrated how BES can be combined with forward osmosis to enhance desalination or achieve self-powered hydrogen production. Mathematical models have been developed to predict the performance of the integrated systems. In Chapter 9, BES have been used as a research platform to understand the fate and removal of antibiotic resistant genes under anaerobic conditions. The studies in this dissertation have collectively demonstrated that BES may hold great promise for energy-efficient water and wastewater treatment. / Ph. D. / Water and energy are prerequisites to life. Every day, a lot of energy and money are spent on treating wastewater and producing fresh water. Bioelectrochemical systems (BES) are new technologies that can treat water and wastewater with low energy consumption. BES typically consist of an anode (where microorganisms break down organic matter) and a cathode, and work like a battery. Currently, BES are only studied in laboratories and not applied in real-world situations, because the performance needs to be improved and fundamentals remain to be better understood. The studies in this dissertation aim to address these problems and make BES toward practice. It has been shown in Chapter 2 that, under high salinity, some bacteria grow faster in the anode and the BES can produce higher electricity. It is difficult to understand the roles of every bacterium with current molecular techniques, and thus statistical methods are applied to estimate their possible functions. In Chapter 3, 4 and 5, three materials have been fabricated and functioned as the catalysts for electricity generation. Chapter 6, 7 and 8 have demonstrated how BES can be combined with forward osmosis, a spontaneous water diffusion process, to enhance desalination or achieve self-powered hydrogen production. Mathematical equations have been combined to simulate the process of biological metabolisms, water diffusion and ion migration. In Chapter 9, BES have been shown to remove antibiotic resistant gene, an emerging contaminant caused by the excessive use of antibiotics. The studies in this dissertation have collectively demonstrated that BES may be the answer to future water and wastewater treatment.

E. coli and Enterococcus were used to determine the fate and survival of fecal indicator bacteria (FIB) in sand and sediments. The microbial source tracking (MST) methods antibiotic resistance analysis (ARA), Bacteroides human-specific primer test, and fluorometry were compared against the FIBs to determine how reliable each method was in detecting the presence of human fecal contamination. Two phases (Summer 2009 and 2010) were evaluated based on the type of contamination event. A combined sewage overflow (CSO) event was simulated in Phase I, where large amounts of influent were added to sand and bay water columns over 1 to 4 days. In 2010, a low volume sewage leak was simulated in which smaller doses of influent were added to sand and bay water columns over a period of 5 to 15 days. Within each of the phases, both non- and re-circulated columns were also evaluated. Evaluation of FIB survival indicated that Enterococcus was able to stabilize and re-grow in the water and at the sediment/water interface within the Phase I non-circulated columns. E. coli was unable to re-grow and/or stabilize within any environment. Comparisons between the ARA and the FIBs revealed a large majority of isolates identified as coming from either bird or wildlife sources. Human sources were identified but at much lower concentrations than expected. Bacteroides results indicated strong relationships between the increase of FIB concentrations and the presence of the human-specific Bacteroides. Fluorometry results did not indicate any relationship with the FIBs. Unexpectedly, fluorometry readings increased as time progressed indicating that another compound was present that fluoresced at the same wavelength as optical brighteners (OBs). This project was one of the first to study the differences related to two different pollution events (CSO vs. sewage leak) while also evaluating what happens to pollution as it settles into the sediment. It was also unique because it compared bacterial (ARA), molecular (Bacteroides), and chemical (fluorometry) MST methods. / Master of Science

Host-associated microbial communities, also known as microbiomes, are essential to the health of their hosts, and disturbance of these communities can negatively impact host fitness. The honey bee gut microbiome is a relatively simple host-associated community that makes an excellent model system for studying microbiome stability. In addition, honey bees are essential agricultural pollinators, so factors that impact their health are important for food security. The presented research focused on the stability of the honey bee gut microbiome in response to disturbance from the antibiotic tetracycline. Tetracycline was chosen because it is the most commonly used antibiotic in beekeeping, and may have negative effects on bees through the disruption of their gut microbiomes. The first study presents a new fecal sampling method for studying the honey bee gut microbiome of individual bees over time. This method accurately represented bacterial community structure in the gut microbiome as determined with 16S rRNA gene amplicon sequencing, as fecal and whole gut samples did not differ significantly for individual bees. The fecal sampling technique was then used to examine changes to individual honey bee gut bacterial communities before and after tetracycline exposure. Minimal differences in gut community structure were detected prior to and five days after tetracycline treatment. However, there was variability in how individual gut microbiomes were affected by tetracycline treatment, highlighting the importance of intraspecific variation in response to disturbance. The second study investigated whether the timing of disturbance during a host's life impacts microbiome community stability. Newly emerged bees were treated with tetracycline, returned to their hive, and recollected 7 or 14 days later. The gut communities of the bees were then characterized using 16S rRNA gene amplicon sequencing. Gut microbiome structure of bees treated with tetracycline at emergence differed from controls both 7 and 14 days after emergence, with the antibiotic-treated bees having lower community richness overall. This study showed that early life disturbance of host-associated microbial communities can influence microbiome structure later in life. The final study describes the occurrence of antibiotic resistance genes (ARGs) in honey bee gut bacterial symbionts from hives across the US. Honey bee gut metagenomes were sampled from hives at 13 apiaries located in a transect from Virginia to Washington, and ARG presence was assessed across the sites. We also specifically quantified the abundances of two common tetracycline resistance genes (tet(B) and tet(M)) across apiaries. ARGs, both for antibiotics used in beekeeping and unrelated antibiotics, were detected in honey bee gut bacteria from all apiaries. Tetracycline resistance genes were the most common across all apiaries, and the abundance of two tetracycline resistance genes varied by apiary. Members of the honey bee gut microbiome contained different proportions of ARGs, but taxa within a single family contained similar proportions, possibly indicating phylogeny plays a role in ARG accumulation. In particular, Gilliamella and Frischella, both in the family Orbaceae, contained the highest percentages of ARGs. The results from this study suggest honey bee bacteria act as reservoirs of ARGs. Overall, the presented research contributes to the field of biology by highlighting the importance of intraspecific variation in host-associated microbial communities and presenting a new method for studying honey bee gut microbiome variation at the individual-level, showing that early life events in honey bees influence microbiome development, and suggesting that honey bee bacterial symbionts have adapted to deal with antibiotic disturbance through the accumulation of ARGs. / Doctor of Philosophy / Nearly all animals, including honey bees, have communities of bacteria that live on and in them. These communities, called microbiomes, are often essential to the health of their hosts. For instance, communities of gut bacteria can be important for breaking down food for digestion. Honey bees have approximately 10 bacterial species that consistently live in their guts and provide these types of services to their host. As with many bacterial communities, these beneficial bacteria can be impacted by exposure to antibiotics, even though antibiotics can also be important for treating or preventing dangerous bacterial infections. In honey bee hives, the antibiotic tetracycline is used to prevent bacterial disease. However, tetracycline may simultaneously be negatively impacting colony health through disruption of the honey bee gut microbiome. The goal of the presented work was to understand how tetracycline impacts the honey bee gut microbiome. In my first chapter, I demonstrate a new fecal sampling method that will allow us to understand how gut microbiomes from individual bees change over time. I first compared the bacteria found in fecal samples to those in the whole guts of bees and found that the bacterial communities of the fecal samples and guts were very similar, indicating that fecal sampling is a good method for studying the honey bee gut microbiome. I then used my fecal sampling method to determine how individual honey bee gut microbiomes respond to antibiotic disturbance over time. I collected fecal samples from adult bees prior to treatment, treated the bees with tetracycline, and after five days of being maintained in the lab, recollected fecal samples. My results showed few changes to the bacterial communities before and after treatment, suggesting some honey bee gut microbiomes may be resistant to tetracycline. In my second chapter, I addressed whether exposure to antibiotics early in life had long-term impacts on the gut microbiome. I treated bees at the start of adulthood with tetracycline, returned the bees to their hive for 7 or 14 days, and assessed their microbiome. Tetracycline treatment at the beginning of adulthood changed the gut microbiome later in life, as the microbiomes of tetracycline-treated bees and controls differed from one another both 7 and 14 days after exposure. This chapter shows that disturbances to microbiomes during early life can also affect microbiomes later. My third chapter addressed how honey bee bacteria have adapted to antibiotic use by identifying antibiotic resistance genes (ARGs) in honey bee gut bacteria from 13 hives located in a transect across the US from the state of Washington to Virginia. I found a variety of antibiotic resistance genes in honey bee gut bacteria, both associated with beekeeping and likely environmental contamination. The prevalence of antibiotic resistance genes in honey bee bacteria may help us track antibiotic resistance in the environment. Ultimately, my dissertation contributes to our understanding of how antibiotic use affects honey bees by changing their gut microbiome.