Transitions in interaction landscapes of multidrug combinations

Abstract

Drug combinations are a promising strategy to increase killing efficiency and to decrease the likelihood of evolving resistance. A major challenge is to gain a detailed understanding of how drugs interact in a dose-specific manner, especially for interactions involving more than two drugs. Here we introduce a direct and intuitive visual representation that we term \"interaction landscapes\". We use these landscapes to clearly show that the interaction type of two drugs typically transitions smoothly from antagonism to no interaction to synergy as drug doses increase. This finding contradicts prevailing assumptions that interaction type is always the same. Our results, from 56 interaction landscapes, are derived from all possible three-drug combinations among 8 antibiotics, each varied across a range of 7 concentrations and applied to a pathogenic Escherichia coli strain. Such comprehensive data and analysis are only recently possible through implementation of an automated high-throughput drug-delivery system and an explicit mathematical framework that disentangles pairwise versus three-way as well as net (any effect) versus emergent (requiring all three drugs) interactions. Altogether, these landscapes partly capture and encapsulate selective pressures that correspond to different dose regions and could help optimize treatment strategies. Consequently, interaction landscapes have profound consequences for choosing effective drug-dose combinations because there are regions where small changes in dose can cause large changes in pathogen killing efficiency and selective pressure.