Aulin, L. B. S. | bioRxiv Science

bioRxiv2021

Design principles of collateral sensitivity-based dosing strategies

Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance.

pharmacology and toxicology↗

bioRxiv2020

Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone-resistance evolution

Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity towards other antibiotics, offers novel treatment opportunities to constrain or reverse the evolution of antibiotic-resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here we address this issue in the Gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles, and their combinations, that confer resistance to fluoroquinolones. We integrated these results in a mathematical model which allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic specific pharmacodynamics, revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies. SignificanceA promising strategy to overcome the evolution of antibiotic resistant bacteria is to use collateral sensitivity-informed antibiotic treatments that rely on cycling or mixing of antibiotics, such that that resistance towards one antibiotic confers increased sensitivity to the other. Here, focusing on multi-step fluoroquinolone resistance in Streptococcus pneumoniae, we show that antibiotic-resistance induces diverse collateral responses whose magnitude and direction are determined by allelic identity. Using mathematical simulations, we show that these effects can be exploited via combination treatment regimens to suppress the de novo emergence of resistance during treatment.

microbiology↗