This episode features Dr. Marjon de Vos PhD from the University of Groningen (the Netherlands) speaking about microbial ecology and evolution, and in particular how these affect antimicrobial resistance. She studies the urobiome as well as the factors that contribute to urinary tract infections and successful treatment of these infections with antibiotics. Her lab combines molecular biology techniques with phenotypic and growth measurements, as well as computational modeling. She has found evidence of microbial interactions mediating evolutionary potential of microorganisms – for example, in vitro experiments showed that in the presence of Enterococcus, E. coli speeds up its rate of developing antimicrobial resistance. Thus, interactions within the bacterial ecosystem may affect pathogens’ sensitivity to antimicrobials. Prebiotics are a potential intervention: if bacteria that make a pathogen more susceptible to antimicrobials are already present in the urobiome, their numbers could be enhanced. Probiotics are another possibility. From a One Health perspective, such approaches are important to explore because they support antimicrobial stewardship and help maintain control of antimicrobials in the environment overall. Episode abbreviations and links: Preprint describing pathogens’ differing rates and evolutionary trajectories towards antibiotic resistance based on other microbes present: Microbial interactions affect the tempo and mode of antibiotic resistance evolution Paper describing ecological interactions between different bacterial species in urinary tract infections: Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections Research showing how 5 different bacteria affect the conjugation efficiency of E. coli: Community context influences the conjugation efficiency of Escherichia coli  About Dr. Marjon de Vos PhD: We investigate ecological and evolutionary processes in microbial communities, with a focus on infectious contexts. Our goal is to unravel the genotype–phenotype–fitness relationships within (evolving) communities and to identify the ecological factors that drive microbial evolution. To achieve this, we combine molecular biology techniques with phenotypic and growth measurements, as well as computational modeling. Our research places special emphasis on the urobiome and urinary tract infections in postmenopausal women, as well as on sepsis. By uncovering the fundamental ecological and evolutionary dynamics of microbial communities in infectious diseases, we aim to contribute to the development of strategies that alleviate infections and help curb the emergence and spread of antibiotic resistance.