Antibiotics change the population growth rate heterogeneity and morphology of bacteria. - Morten Kals; Emma Kals; Jurij Kotar; Allen Donald; Leonardo Mancini; Pietro Cicuta (PLoS Pathogens)
A better understanding of the system-level effects of antibiotics on bacterial cells is essential to address the growing challenge of antibiotic resistance. Utilising Multipad Agarose Plate (MAP) platforms, we monitor the growth rate and cell morphology of three clinically relevant species (E.coli, S.aureus and P.aeruginosa) following exposure to 14 antibiotics across 11 concentrations (31 microbe-antibiotic combinations in total). Our results reveal a consistent increase in population growth rate heterogeneity (PGRH) as drug concentrations approach the minimum inhibitory concentration (MIC). Strikingly, the magnitude of this heterogeneity correlates with the functional distance between the ribosome and the specific cellular processes targeted by the antibiotics. Among the seven antibiotic classes studied, protein synthesis inhibitors and disruptors cause the lowest PGRH, while heterogeneity progressively increases with RNA synthesis inhibitors, DNA replication inhibitors, cell membrane disruptors and cell wall synthesis inhibitors. Because the ribosome is central to growth rate control, we hypothesize that heterogeneity might arise at the system level as a result of the propagation of damage to protein synthesis. Low heterogeneity is desirable from a clinical perspective, as high heterogeneity is often associated with persistence and treatment survival. Additionally, we observed a strong correlation between morphological alterations and growth inhibition across all antibiotics and species tested. This led to the development of a novel morphological parameter, MOR50, which enables rapid estimation of MIC for antibiotic susceptibility testing (AST) with a single snapshot after just 2.5 hours of incubation. In addition to introducing a novel, resource-efficient and rapid AST method, our findings shed new light on the system-level effects of antibiotic perturbations on bacteria, which might inform treatment design.