Microbial interactions as key players shaping the emergence and spread of de novo resistance mutations

Antibiotic resistance and the microbiome are two of the most prominent and highly active research areas currently in microbiology. However, these studies are commonly siloed. Research into antibiotic resistance often takes a highly pathogenic-centric view, and microbiome studies typically assess changes in community composition at the genus or species level, rather than at the level of small changes in bacterial genotype that often underpin rapid and significant changes in antibiotic resistance. One of the major mechanisms of antibiotic resistance evolution is via the acquisition of de novo resistance mutations, spontaneous mutations that occur randomly and provide a selective advantage in the presence of antibiotics. In this perspective, we address how interactions within the microbiome can shape the emergence and spread of de novo resistance mutations. We outline existing theoretical and empirical support for how microbial interactions have the potential to influence (i) the probability of de novo resistance mutations emerging, (ii) the fitness costs associated with new resistance mutations and (iii) the long-term selection against resistance and the ability of resistant mutants to transmit to new sites. Existing evolutionary theory may help us predict how microbial interactions will impact the probability of resistance mutations emerging, through understanding how microbial communities will impact pathogen population size, mutation rates and the supply of genetic variation. While a number of these links are simple and intuitive, there is a need for empirical data to understand how the complexity of interactions that exist within a microbial community at any one time come together to shape the evolution of antibiotic resistance. Future research in this field has the potential to inform the development of novel strategies to combat antibiotic resistance based on manipulating microbial interactions.