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.

La flore microbienne est un ensemble de micro-organismes comme les bactéries, archées, eucaryotes inférieurs et virus, jouant un rôle important dans l’équilibre d’un écosystème. Cette flore reste encore mal définie car en 2012, seules ~30% des micro-organismes de la flore intestinale humaine étaient caractérisés, et moins de 50% des micro-organismes de la flore fromagère traditionnelle étaient caractérisés au niveau fonctionnel. Depuis 2006, les séquenceurs à ADN de seconde génération permettent d’analyser directement le contenu génique d’un prélèvement de flore sans contrainte d’isolement ou de culture. Toutefois, les séquences d’ADN générées ne sont pas structurées en génome et sont hautement fragmentées, freinant considérablement l’analyse et l’exploitation de ces données. Dans ce travail, nous avons développé de nouvelles méthodes dites de métagénomiques quantitatives, car elles permettent de regrouper les courtes séquences d’ADN ayant la même abondance au sein de plusieurs échantillons métagénomiques, pouvant provenir d’une même espèce microbienne.Au niveau du microbiote intestinal humain, nous avons structuré un catalogue de 3,9 millions de gènes de la flore intestinale humaine en 741 unités ou « clusters » correspondant à des génomes de bactéries, d’archées et d’eucaryotes, que nous appelons espèces métagénomiques (MGS) et 6640 unités correspondant principalement à des génomes de virus, plasmides et divers ilots génomiques comme des CRISPR, que nous appelons unités métagénomiques (MGU). Cette méthode de structuration a ensuite été utilisée pour faciliter des analyses d’associations de la composition de la flore intestinale avec des maladies humaines comme la maladie de Crohn, l’obésité ou le diabète de type 2. Enfin, au niveau des flores alimentaires, nos méthodes ont été utilisées pour constituer un catalogue de 134 génomes d’espèces bactériennes fromagères et caractériser la flore de surface de fromages traditionnels. Ceci nous a permis de détecter la présence de nouvelles bactéries alimentaires, pouvant enrichir la liste des bactéries à possible intérêt technologique dans les produits laitiers fermentés. / The microbial flora is a micro-organism complex containing for example bacteria, archaea, lower eukaryotes and viruses, which play an important role in ecosystem equilibrium. This flora remains poorly defined as in 2012, only ~30% of the intestinal flora micro-organisms have been characterized, and less than 50% of traditional cheese floras were characterized at the functional level. Since 2006, the second generation of DNA sequencers have allowed the direct analysis of the genetic content from a microbial flora sample without isolation or culture limitation. However, the DNA reads generated are not structured with respect to genomes and also are highly fragmented, slowing down dramatically the exploitation and analysis of these data.In this work, a new methodology based on quantitative metagenomic are described., This allows the clustering of short DNA sequences with the same abundance in multiple metagenomic samples, which should originate from the same microbial species. A 3.9 million gene catalog has been built from the human intestinal tract microbiota and divided into 741 units or clusters corresponding to bacteria, archaea and eukaryote genomes. These have been defined as metagenomic species (MGS) and 6640 units of them corresponds mainly to viral genomes, plasmids and genetic islands like CRISPR, with the sub-name of metagenomic units (MGU). This methodology was then used to facilitate the association analysis of the intestinal flora composition with human diseases such as Crohn’s disease, obesity or type 2 diabetes. Within, the alimentary flora, our methods have also been used to constitute a 134 genomic catalog of cheese bacteria and characterize them from the surface of traditional cheeses. This allowed the detection of new alimentary bacteria, that will enriched the list of bacteria with potential interest for the commercial exploitation of fermented products.