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.

The main focus of this research was the development of microfluidic technology for ultrasensitive and fast molecular analysis of cells. Chromatin immunoprecipitation (ChIP) assay followed by next generation sequencing serves as the primary technique to characterize the genomic locations associated with histone modifications. However, conventional ChIP-seq assay requires large numbers of cells. We demonstrate a novel microfluidics-based ChIP-seq assay which dramatically reduced the required cell number. Coupled with next generation sequencing, the assay permitted the analysis of histone modifications at the whole genome from as few as ~100 cells. Using the same device, we demonstrated that MeDIP-seq with tiny amount of DNA (<5ng) generated high quality genome-wide profiles of DNA methylation. Off-chip sonication often leads to sample loss due to multiple tube transferring. In addition, conventional sonicators are not able to manipulate samples with small volume. We developed a novel microfluidic sonicator, which is able to achieve on-chip DNA/chromatin shearing into ideal fragment size (100~600bp) for both chromatin immunoprecipitation (ChIP) and methylated DNA immunoprecipitation (MeDIP). The integrated on-chip sonication followed by immunoprecipitation (IP) reaction can significantly reduce sample loss and contamination. Simple and accessible detection methods that can rapidly screen a large cell population with single cell resolution have been seriously lacking. We demonstrate a simple protocol for detecting translocation of native proteins using a common flow cytometer which detects fluorescence intensity without imaging. Using our approach, we successfully detected the translocation of native NF-kappa B (an important transcription factor) at its native expression level and examine the temporal dynamics in the process. Droplets with encapsulated beads and cells have been increasingly used for studying molecular and cellular biology. However, a mixed population of droplets with an uneven number or type of encapsulated particles is resulted and used for screening. We developed a fluorescence-activated microfluidic droplet sorter that integrated a simple deflection mechanism. By passing droplets through a narrow interrogation channel, the encapsulated particles were detected individually. The microcontroller conducted the computation to determine the number and type of encapsulated particles in each droplet and made the sorting decision. Our results showed high efficiency and accuracy for sorting and enrichment. / Ph. D.

Microfluidics has revolutionized how molecular biology studies are conducted. It permits profiling of genomic and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this thesis, we focus on three projects (diffusion-based PCR, MID-RRBS, and SurfaceChIP-seq), which improved the sensitivities of conventional assays by coupling with microfluidic technology. MID-RRBS and SurfaceChIP-seq projects were designed to profiling genome-wide DNA methylation and histone modifications, respectively. These assays dramatically improved the sensitivities of conventional approaches over 1000 times without compromising genomic coverages. We applied these assays to examine the neuronal/glial nuclei isolated from mouse brain tissues. We successfully identified the distinctive epigenomic signatures from neurons and glia. Another focus of this thesis is applying electrical field to investigate the intracellular contents. We report two projects, drug delivery to encapsulated bacteria and mRNA extraction under ultra-high electrical field intensity. We envision rapid growth in these directions, driven by the needs for testing scarce primary cells samples from patients in the context of precision medicine. / Ph. D.

The shift of medical technology from a doctor's application of individualized medicine toward precision medicine has been accelerated by the advent of Next Generation Sequencing. Individualized medicine is where a doctor tries to understand the intricacies of a patient's medical state, where precision medicine uses a wealth of data to understand the individuality of a patient on a biological level to determine treatment course. Next Generation Sequencing allows for the collection of genome wide analyses such as genomic, transcriptomic, and epigenomic sequencing, which provides the backbone of the data driven precision medicine. In order to obtain and use this data, it needs to be produced from minimal amounts of patient tissue, such as the amount from a needle biopsy. In order to perform so many different assays it is paramount that we develop high sensitivity methodologies, such that we can gain an understanding of the patient's physiology without causing much discomfort in gathering large amounts of sample. In pursuit of making more tests, data, and assays available for use in precision medicine, we have developed 3 different microfluidic technologies, which automate and simplify the assays needed for the data collection at a high sensitivity, as well as a versatile platform for therapeutic production. First, we developed a epigenomic assay for chromatin immunoprecipitation, which gives us information on histone modifications across the genome. These histone modifications heavily impact gene expression and how the chromatin is organized, as well promoting or inhibiting transcription of genes. Our technology allowed us to perform multiple parallel assays from as few as 50 cells quickly and reliably using our fluidized bed technology. Next, we developed a library preparation system, which reduces the cost of library preparation by 20x and reduces operator pipetting by 100x. Our system uses a droplet based reactor to quickly and reliably prepare sequencing libraries using the lowest amount of DNA to date, 10 pg. Finally, we designed a therapeutics-on-a-chip platform which is capable of producing clinically relevant proteins on demand from temperature stable components. Using our system, we are capable of producing a number of different therapeutics on demand quickly without rearrangement of the system. / Doctor of Philosophy / Technical advances in the healthcare industry have made a range of new data available to physicians and patients. Home use DNA testing kits have made it possible to examine one’s predisposition to certain genetic diseases. Using these advanced methods, we are able to gain insights into a patient’s disease state where we were previously unable. Unfortunately, some of these new analyses currently require large amounts of patient sample, which make the examinations largely impractical to perform. In order to overcome the sample requirements, which make these analyses impractical, we develop microscale reactor systems capable of reducing the amount of material required for these new analyses. Here I demonstrate our developed technologies to automate 3 different processes aimed at enabling the study of protein-DNA interactions and produce therapeutics at the point of care. First, we developed an analytical system to study protein-DNA interactions (which are important to understanding patient responses to treatment), that allow for parallel analyses which can be done with sample from less than one needle biopsy, where existing methods would require dozens or more (50 vs 10,000,000 cells.) Next, we developed automated system for preparing DNA sequencing libraries using as little as 10 pg DNA (~2 cells of DNA). The device run multiple reactions simultaneously while reducing batch to batch variation and operator hands-on time. Finally, we developed a v Therapeutics-On-a-Chip platform that produces clinically relevant therapeutic proteins in clinically relevant dosages using a cell-free approach, while saving the trouble and cost associated with protein storage and transportation.

The innate immune response to lipopolysaccharide (LPS) mediated by toll-like receptor 4 (TLR4) contributes substantially to the morbidity of equine gastrointestinal disease, neonatal sepsis and other diseases. MicroRNAs (miRNAs), small non-coding RNA molecules acting as post-transcriptional regulators of gene expression, have key roles in TLR4 signaling regulation in other species. The central hypothesis of this study was that LPS induces differential expression of miRNAs in equine peripheral blood mononuclear cells (PBMCs). PBMCs were isolated from healthy adult horses and cultured with LPS or medium only for 2, 4 and 8 hours. Concentrations of inflammatory cytokines were measured in supernatants by immunoassay. Illumina Next-Generation Sequencing of the miRNA transcriptome was performed in PBMCs at 0, 2 and 4 hours. Selected expression changes were verified by qRT-PCR. 327 mature miRNAs were detected in equine PBMCs. Only miR-155 was significantly upregulated by LPS. 9 miRNAs showed statistically significant expression changes with time. Tumor necrosis factor-α concentration was significantly higher in supernatants from LPS-treated cells than controls from 2 hours, while interleukin-10 and interferon-γ were increased at 8 hours. miR-155 expression was correlated to all three cytokines. These data provide a foundation for future research into miRNA involvement in equine inflammatory responses. miR-155 is the principal LPS-induced miRNA in horses. Bioinformatic target predictions support roles in regulation of innate and adaptive immune responses including TLR4 signaling, as in humans. It is thus likely to influence the acute inflammatory response to LPS. Further research will be necessary to establish its role in naturally occurring disease. / Master of Science

Since the dawn of the genomics era, the genetics of numerous human disorders has been understood which has led to improvements in targeted therapeutics. However, the focus of most research has been primarily on protein coding genes, which account for only 2% of the entire genome, leaving much of the remaining genome relatively unstudied. In particular, repetitive sequences, called microsatellites (MST), which are tandem repeats of 1 to 6 bases, are known to be mutational hotspots and have been linked to diseases, such as Huntington disease and Fragile X syndrome. This work represents a significant effort towards closing this knowledge gap. Specifically, we developed a next generation sequencing based enrichment method along with the supporting computational pipeline for detecting novel MST sequences in the human genome. Using this global MST enrichment protocol, we have identified 790 novel sequences. Analysis of these novel sequences has identified previously unknown functional elements, demonstrating its potential for aiding in the completion of the euchromatic DNA. We also developed a disease risk diagnostic using a novel target specific enrichment method that produces high resolution MST sequencing data that has the potential to validate, for the first time, the link between MST genotype variation and cancer. Combined with publicly available exome datasets of non-small cell lung cancer and 1000 genomes project, the target specific MST enrichment method uncovered a signature set of 21 MST loci that can differentiate between lung cancer and non-cancer control samples with a sensitivity ratio of 0.93. Finally, to understand the molecular causes of MST instability, we analyzed genomic variants and gene expression data for an autosomal recessive disorder, Fanconi anemia (FA). This first of its kind study quantified the heterogeneity of FA cells and demonstrated the possibility of utilizing the DNA crosslink repair dysfunctional FA cells as a suitable system to further study the causes of MST instability. / Ph. D.

Background: Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression. Methods: We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan–Meier estimator, log-rank test, and Cox regression. Results: Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR . These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05). Conclusions: Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

No / Transposable elements (TEs), such as endogenous retroviruses (ERVs), are common in the genomes of vertebrates. ERVs result from retroviral infections of germ-line cells, and once integrated into host DNA they become part of the host's heritable genetic material. ERVs have been ascribed positive effects on host physiology such as the generation of novel, adaptive genetic variation and resistance to infection, as well as negative effects as agents of tumorigenesis and disease. The avian leukosis virus subgroup E family (ALVE) of endogenous viruses of chickens has been used as a model system for studying the effects of ERVs on host physiology, and approximately 30 distinct ALVE proviruses have been described in the Gallus gallus genome. In this report we describe the development of a software tool, which we call Vermillion, and the use of this tool in combination with targeted next-generation sequencing (NGS) to increase the number of known proviruses belonging to the ALVE family of ERVs in the chicken genome by 4-fold, including expanding the number of known ALVE elements on chromosome 1 (Gga1) from the current 9 to a total of 40. Although we focused on the discovery of ALVE elements in chickens, with appropriate selection of target sequences Vermillion can be used to develop profiles of other families of ERVs and TEs in chickens as well as in species other than the chicken. / Financial support was provided by the EW GROUP, as well as grants from the Canada Foundation for Innovation, Canada Research Chairs Program, and the Natural Sciences and Engineering Council of Canada to RGB, and Canada Institutes of Health Research funding to MGIL and CJM.

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