Mutation bias influences the emergence and effects of antibiotic resistance

Abstract

Evolution of antibiotic resistance is a major global public health problem. Rapid emergence of antibiotic resistance is often linked to hypermutator bacteria with defective DNA repair, leading to high mutation rates that are broadly advantageous. However, depending on which DNA repair pathway is dysfunctional, mutators may sample only specific types of mutations at a higher rate. Thus, their mutation spectrum can be biased towards specific mutation types, influencing the identity of resistance mutations. Under strong antibiotic selection, an overall high mutation rate should generally shorten the time to sample a resistance mutation and increase the probability of resistance. However, recent work suggests that the mutation rate for specific types of mutations in target genes that drive high resistance is more important than the overall mutation rate. To systematically test this prediction, we exposed Escherichia coli mutators with varying mutation rates and spectra to antibiotics targeting different cellular functions. For each strain, we determined the highest antibiotic concentration at which resistance could emerge overnight, quantifying both the magnitude and probability of resistance. High level antibiotic resistance was generally better predicted by specific rather than overall mutation rate, and resistance mutations matched the mutation spectrum of the respective mutator. Despite the varying magnitude of resistance, at the highest antibiotic concentration survived by each strain, the respective resistance mutations were generally costly in the absence of antibiotic. Given that mutators often arise in laboratory, natural, and clinical settings under antibiotic selection, we suggest that their mutation spectra deserve more attention.