Thèse Explorer le Rôle des Phages dans la Sélection et la Dissémination des Plasmides Codant la Résistance aux Antimicrobien H/F - Doctorat.Gouv.Fr

Établissement : Université Claude Bernard Lyon 1 École doctorale : E2M2 - Evolution Ecosystèmes Microbiologie Modélisation Laboratoire de recherche : MMSB - MICROBIOLOGIE MOLECULAIRE ET BIOCHIMIE STRUCTURALE Direction de la thèse : Anne CHEVALLEREAU ORCID 0000000333697468 Début de la thèse : 2026-10-01 Date limite de candidature : 2026-07-31T23:59:59 Ce projet de thèse aborde le défi urgent de santé publique que représente la résistance aux antimicrobiens (RAM), en étudiant le rôle des bactériophages (phages) dans la dissémination des plasmides porteurs de gènes de résistance. Les infections bactériennes causent des millions de décès chaque année, et la RAM aggrave cette crise, souvent sous l'effet de plasmides qui propagent à la fois des gènes de résistance et de virulence. Des découvertes récentes révèlent que les plasmides codent fréquemment des systèmes de défense anti-phages, suggérant une possible co-sélection entre la RAM et la résistance aux phages.Le projet vise à caractériser l'écologie et la prévalence des plasmides défensifs, en particulier ceux porteurs de gènes de RAM, et à déterminer comment les phages influencent leur propagation. Grâce à des analyses bioinformatiques de plus de 60 000 séquences de plasmides, l'étude identifiera les liens entre les familles de plasmides, les systèmes de défense et les gènes de RAM, tout en cartographiant leur distribution écologique.Sur le plan expérimental, le projet utilisera des modèles comme Escherichia coli et le phage T7 pour tester comment les caractéristiques des plasmides - telles que les taux de transfert horizontal et les mécanismes de défense - affectent leur dissémination sous la pression des phages. En combinant des approches génomiques et expérimentales, cette recherche cherche à élucider comment les phages favorisent la persistance des plasmides porteurs de RAM, offrant ainsi des pistes pour la thérapie par phages et des stratégies visant à limiter la propagation de la résistance. Bacterial infections account for more than 13 million deaths in 20191. While antibiotics remain the standard treatment, their efficacy has been steadily declining due to the global spread of antimicrobial resistance (AMR) now recognized as one of most pressing challenges in public health. Emerging pathogens are typically defined as microorganisms whose incidence has increased in recent decades or threatens to increase in the near future. In bacteria, these emergences are often associated with the recent acquisition of novel functions, including virulence determinants and AMR. In the last decade, several emerging bacterial pathogens already exhibited resistance to multiple antibiotics, or rapidly acquired it after being recognized as an emerging pathogen. This pattern is largely driven by plasmids, which act as major vectors for both AMR genes and virulence factors. They act as facilitators of the rapid adaptation of bacterial populations to clinical and environmental pressures. Therefore, understanding the ecological and evolutionary aspects that shape the spread, maintenance and loss of plasmids is crucial to better comprehend the emergence of pathogenicity and drug resistance. To combat drug resistant bacteria, intense research efforts are made to develop alternative solutions, including phage therapy, the use of bacterial viruses. Phages are ubiquitous and highly abundant viral entities that impose pervasive selective pressures structuring microbial communities and shaping bacterial genome evolution2. To resist phage infection, bacteria have evolved a wide range of mechanisms, ranging from cell-surface modifications to prevent phage adsorption to dedicated intracellular anti-phage defence systems. The recent discoveries of over 300 new defence systems profoundly reshaped our understanding of prokaryotic immunity3. A key, yet underappreciated, feature of defence systems is their tight coupling to horizontal gene transfer. Defence genes frequently cluster within genomes and vary extensively, even among closely related strains, indicating high mobility. Notably, defence systems are commonly encoded by mobile genetic elements (MGE), including plasmids, prophages, and satellite elements. This pattern supports a conceptual shift in which defence systems evolve not only through bacterium-phage arms races, but also through interactions and competition among MGE for access to host resources4, consistent with the view that MGE can follow evolutionary trajectories partly decoupled from those of their bacterial hosts5.Among MGE, plasmids emerge as central yet insufficiently studied vectors of anti-phage defence systems. Defensive plasmids, defined as plasmid encoding defence systems, have been reported sporadically6-8. A recent study focused on Escherichia coli found that 41% of plasmids carry defence genes9. Extending these analyses across taxa and environments, our preliminary analyses indicate that 30% of plasmids (n=62 577) encode at least one defence system. Notably, among plasmids that encode AMR genes (n=13 078), 55% also encode anti-phage resistance genes, suggesting a potential strong co-selection of these two traits. These findings indicate that phages could be key drivers of the spread and maintenance of AMR-carrying plasmids. However, this hypothesis has not been explored, because, to date, very few studies have considered the tripartite bacteria-phage-plasmid interactions10-12. This PhD project aims to explore how phages influence plasmid dissemination Objective 1: Characterize the ecology and prevalence of defensive plasmids We will first provide a comprehensive overview of the defence genes associated with AMR-carrying plasmids. First, we will look for associations between plasmid carrying defence systems and antibiotic resistance genes, which may underscore co-selection dynamics. We will test whether antibiotic resistance genes preferentially co-occur with particular defence types, and whether certain plasmid families are enriched in both AMR and anti-phage defence genes. We will further examine their association with ecological contexts (environmental, clinical, animal, water systems, etc.) and link these patterns to plasmid epidemiological data. Finally, we will characterize the functional traits of plasmids carrying AMR and anti-phage defence genes, focusing on plasticity, mobility, and host range. This will allow us to assess their potential to acquire and disseminate adaptive genes, such as virulence factors and heavy metal resistance.Objective 2: Determine how phages influence plasmid dissemination and how ecological parameters shape their interaction. We first aim to generate proof of concept results using a well characterised model system, before testing the generalisability of our results. We will focus on the model conjugative plasmid F that encodes the PifAC anti-phage defence system, protecting its Escherichia coli host from infection by the model phage T7. The PifAC operates through an Abortive infection mechanism, by triggering host cell death or dormancy to block phage replication and are therefore extremely costly at the individual level13. We will test whether the spread of plasmid F is favoured, compared to the defenceless isogenic plasmid, in a bacterial host population attacked by virulent phages. Furthermore, we will assess how plasmid functional traits influence their spread in the presence of phages. Objective 1: The aim is to identify plasmid families carrying both AMR and anti-phage defence genes and identify the ecological habitats in which these families occur. Once these families are identified, we will perform an in-depth characterization of their functional traits (e.g mobility, plasticity, and host range). This analysis will provide insight into their biology and ecological distribution, and how these traits correlate with their persistence across environments. Our approach includes:(i) Typing plasmids into families based on established classification schemes, such as incompatibility groups and Plasmid Taxonomic Units14.(ii) Screening plasmids for known defence systems and antibiotic resistance genes using dedicated tools such as DefenseFinder 15 and AMRFinder16.(iii) Performing statistical analyses to identify significant associations between specific plasmid families, defence systems, and antibiotic resistance genes. These analyses will identify plasmid families associated with defence systems and identify potential co-selection dynamics between antibiotic resistance genes and phage predation.(iv) Analysing ecological distribution by searching plasmid families carrying AMR genes and anti-phage defence systems within diverse habitats.(v) Characterizing the functional traits of plasmids carrying AMR and anti-phage defence genes. This will allow us to assess the potential of these plasmids to acquire and spread adaptive genes To this end, we will use over 60,000 complete and high-quality plasmid sequences available in public databases (e.g RefSeq). We will initially focus exclusively on complete plasmids to ensure a robust genomic analysis. After classifying these plasmids, we will screen for defense genes and antibiotic resistance genes. Statistical association tests will highlight plasmid families significantly enriched with defense mechanisms and antibiotic resistance. Furthermore, we will identify co-occurrence patterns of these genes within plasmid genomes to identify couples that co-occur more than expected by chance.Once key plasmid families are identified, we will define robust genomic markers by computing core genomes for each plasmid families. These markers will then be used to screen high-quality publicly available metagenomes from MGnify17. Because MGnify datasets are organized by biome, this strategy will allow us to pinpoint ecological habitats where defensive plasmids spread and persist.Objective 2: The aim is to measure the spread of conjugative plasmid F in the presence of phage T7. Whether a defensive plasmid effectively spreads in a bacterial population attacked by phages depends on many parameters, including plasmid traits (e.g., horizontal transfer rate, defensive strategy), phage traits (e.g., reproductive rate), host traits (genetic background, which influences plasmid acquisition and maintenance), and ecological factors. In the frame of this PhD project, we will primarily focus on the influence of plasmid traits: 1) Horizontal transfer rate will be manipulated by generating a mutant plasmid unable to transfer horizontally (deletion of transfer genes tra). This will enable us to measure the relative importance of vertical transfer (from mother to daughter cells) and horizontal transfer (from one bacterium to a neighbouring bacterium) in the spread of the defensive plasmid within a bacterial population2) Defensive strategy will be manipulated by replacing PifAC by a non-abortive, less costly, defence system (e.g., restriction-modification which cleaves phage DNA).The spread of the plasmid will be measured through conjugation and competition assays (described below). Using these assays, we will compare the invasion dynamics and relative dissemination success of isogenic plasmids:1) with and without defence system to establish that defence genes enhance plasmid dissemination2) with and without functional conjugation machinery to establish that conjugative transfer is a key trait for the success of defensive plasmid.3) with an Abi or with a non-Abi defence system to evaluate how specific defence mechanisms influence plasmid spread.To assess how phages reshape plasmid invasion and competition dynamics, both assays will be performed in the absence and presence of phages introduced at a low multiplicity of infection (MOI This experimental pipeline will be applied to a second phage-plasmid system from clinical origin - readily available in the laboratory - to assess the generalizability of our findings. Conjugation assay to quantify plasmid invasion dynamics: The frequency of plasmid conjugative transfer is quantified using a fluorescence-based reporter assay to distinguish donor, recipient and transconjugant (recipient cell that received the plasmid from a donor cell) subpopulations. The conjugative plasmid encodes a green fluorescent protein (GFP). The donor strain is chromosomally tagged with a red fluorescent protein (RPF), resulting in plasmid donor cells exhibiting a dual red-and-green fluorescence signal (GPF+, RFP+). Upon plasmid transfer into untagged recipient cells (RFP-GFP-), the resulting transconjugant cells express GFP (RPF-GFP+). A plasmid donor strain is co-cultured with an excess of plasmid-free recipient bacteria. At t = 0, 4, and 24 hours post-infection, we analyse donor, recipient, and transconjugant subpopulations through: (i) plating to quantify bacterial viability and subpopulation sizes and (ii) flow cytometry and/or plate reader to determine the relative frequencies of each subpopulation, offering high-resolution tracking of plasmid transfer. Competition assay to measure the relative dissemination success: Two conjugative plasmids competing for transmission within a shared population of recipient cells are tagged with a distinct fluorescent reporter (green or red), allowing their respective dynamics to be followed with high precision. Plasmid donors are co-cultured with a continuously renewed pool of recipient cells and propagated over 100 generations (5 days). Daily quantification of green and red fluorescence provides a direct readout of the relative dissemination success of each plasmid, integrating both horizontal and vertical transmission.

Master en biologie