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Municipal wastewater treatment removes carbon and nutrients from sewage by harnessing a dense microbial community in a biological treatment process. The dynamics of the viral community structure and function through wastewater treatment is not well understood. Viruses are expected to play critical roles in biological wastewater treatment because they are highly abundant, exhibit complex host interactions ranging from predatory to symbiotic, and accelerate host evolution. The lack of rigorous methods for isolating viral communities from environmental samples and quantitative methods for measuring and interpreting viral metagenomes has hindered our understanding of the roles of viruses in the environment, in general, and biological wastewater treatment, in particular. The overall goal of this dissertation research was to develop and apply metagenomic and in silico approaches to explore viral community dynamics through biological wastewater treatment and probe the roles that viruses play on the dissemination and emergence of antibiotic resistance. This dissertation developed rigorous methodologies for studying environmental viromes. To address the issue of virus enrichment from environmental samples, an ultrafiltration approach was compared with an iron chloride flocculation method. Next, to measure the absolute abundances of target viruses in wastewater samples before and after treatment, a rigorous quantitative viral metagenomic method was developed. Specifically, dsDNA and ssDNA standards were added to viral DNA extracts to relate relative and absolute abundances. A bioinformatic pipeline, QuantMeta, was developed to calculate concentrations of targets (e.g., contigs or sequences from databases) and assess target-specific detection thresholds and detect and correct non-specific mapping and assembly errors. QuantMeta was applied to quantitative viromes from wastewater samples and improved quantification confidence and accuracy. QuantMeta is not specific to wastewater viromes and is applicable to whole metagenomes and other environments. These methods were applied to three samples of wastewater influent and secondary effluent collected in December 2020 from a municipal wastewater treatment plant. The wastewater viromes were highly purified for viruses with 75.5-78% of contigs classified as viral. Mean total virus concentrations in influent and secondary effluent were 10.3 and 10.6 log10 gc/mL, respectively, approximately two-orders of magnitude higher than previous concentrations made with viral particle counting-based methods. 12.9% of influent viral populations persisted and replicated through biological treatment to be 10.3 log10 gc/mL more abundant in secondary effluent. Viruses rarely carried antibiotic resistance genes, with only 59 viral populations identified. Finally, compounding effects of phage-host coevolution and antibiotic stress on antibiotic resistance emergence and expression in chemostat environments, such as biological treatment and the gut, was assessed using in silico evolution experiments. An Avida environment was developed that simulated an antibiotic with an evolvable trait to confer antibiotic resistance. Experiments demonstrated that phage-host coevolution accelerated the emergence of antibiotic resistance and the presence of phages and antibiotics occasionally resulted in decreased susceptibility to antibiotics. The results indicate that phages alter outcomes of antibiotic resistance evolution. Overall, this dissertation provides critical tools for quantitative studies of viromes. Their application provides insight on viral community dynamics through wastewater treatment, including their overall abundances, diversity, and potential role in the spread of antimicrobial resistance. The tools developed here can be applied in future studies of viral and microbial communities in metagenomes to directly compare between samples.

Environmental surveillance is a critical tool for combatting public health threats represented by the global COVID-19 pandemic and the continuous increase of antibiotic resistance in pathogens. With its power to detect entire microbial communities, metagenomics-based methods stand out in addressing the need. However, several hurdles remain to be overcome in order to generate actionable interpretations from metagenomic sequencing data for infection prevention. Conceptually and technically, we focus on viability assessment, taxonomic resolution, and quantitative metagenomics, and discuss their current advancements, necessary precautions and directions to further development. We highlight the importance of building solid conceptual frameworks and identifying rational limits to facilitate the application of techniques. We also propose the usage of internal standards as a promising approach to overcome analytical bottlenecks introduced by low biomass samples and the inherent lack of quantitation in metagenomics. Taken together, we hope this perspective will contribute to bringing accurate and consistent metagenomics-based environmental surveillance to the ground.

International audience; The human gut microbiome can now be characterized in unprecedented detail by an approach based on high-throughput sequencing of total stool DNA, that we name quantitative metagenomics. Central to the approach is a catalog that lists all the genes of intestinal microbes that are known -9.9 millions, identified by the analysis of 1267 stool samples. Beyond the gene list, genetic units that carry them begun to be known; many of these correspond to bacterial species that were never isolated and cultured yet. Quantitative metagenomics allows developing powerful algorithms to diagnose a disease, monitor patients and identify individuals at risk to progress towards a disease. This lays ground for developing new approaches to better restore and even preserve the health by modulation of the altered microbiome, which contributes to promote or aggravate a disease.

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.; 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.

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.