How to measure bacterial genome plasticity? A novel time-integrated index helps gather insights on pathogens

Abstract

Genome plasticity can be defined as the capacity of a bacterial population to swiftly gain or lose genes. The time factor plays a fundamental role for the evolutionary success of microbes, particularly when considering pathogens and their tendency to gain antimicrobial resistance factors under the pressure of the extensive use of antibiotics. Multiple metrics have been proposed to provide insights into the gene content repertoire, yet they overlook the temporal component, which has a critical role in determining the adaptation and survival of a bacterial strain. In this study, we introduce a novel index that incorporates the time dimension to assess the rate at which bacteria exchange genes, thus fitting the definition of plasticity. Opposite to available indexes, our method also takes into account the possibility of contiguous genes being transferred together in one single event. We applied our novel index to measure plasticity in three widely studied bacterial species: Klebsiella pneumoniae, Staphylococcus aureus, and Escherichia coli. Our results highlight distinctive plasticity patterns in specific sequence types and clusters, suggesting a possible correlation between heightened genome plasticity and globally recognized high-risk clones. Our approach holds promise as an index for predicting the emergence of strains of potential clinical concern, possibly allowing for timely and more effective interventions. Impact statementHow quickly bacterial populations can acquire new functions is the key to their evolutionary success. This speed, called genome plasticity, is particularly relevant for human pathogens, especially when considering the acquisition of antimicrobial resistance. Today, the availability of large numbers of genomes from public databases makes it possible to develop a way to measure plasticity. However, none is currently available, besides indexes of gene content variability, which do not take into account the rate at which such gene content changes. In this work, we developed a plasticity index, called Flux Of Gene Segments (FOGS), and we tested it on large datasets of bacterial pathogen genomes. Interestingly, the subpopulations of the selected species that showed higher FOGS correspond to globally emerging high-risk clones. Therefore, we suggest that our index might be used not only to detect but also to predict emerging strains of human health concern. Data summaryThe authors confirm that all supporting data, code and protocols have been provided within the article or through supplementary data files.