摘要

抗生素需要在体内多种环境中有效。然而，病原体微环境可对抗生素效力产生显着影响。此外，抗生素越来越多地用于组合以抵抗抗性，然而，微环境对药物组合功效的影响是未知的。为了详尽地探讨不同微环境对药物组合的影响，我们在此开发了一种计算框架 - 基于代谢和基因组学的抗生素治疗方案（MAGENTA）。 MAGENTA使用单个药物的化学基因组谱和代谢紊乱来预测不同微环境中的协同或拮抗药物相互作用。我们通过搜索了72种药物的2556种药物组合，发现抗生素组合在九种不同的环境中对大肠杆菌和鲍曼不动杆菌具有强大的协同作用。 MAGENTA还准确预测了在甘油培养基中生长期间抑菌和杀菌药物组合的功效变化，我们在两种微生物中进行了实验证实。我们的方法分别将糖酵解和乙醛酸途径中的基因鉴定为协同作用和拮抗作用的最佳预测因子。我们的系统方法可以根据病原体微环境定制抗生素疗法。

Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination efficacy is unknown. To exhaustively explore the impact of diverse microenvironments on drug-combinations, here we develop a computational framework-Metabolism And GENomics-based Tailoring of Antibiotic regimens (MAGENTA). MAGENTA uses chemogenomic profiles of individual drugs and metabolic perturbations to predict synergistic or antagonistic drug-interactions in different microenvironments. We uncovered antibiotic combinations with robust synergy across nine distinct environments against both E. coli and A. baumannii by searching through 2556 drug-combinations of 72 drugs. MAGENTA also accurately predicted the change in efficacy of bacteriostatic and bactericidal drug-combinations during growth in glycerol media, which we confirmed experimentally in both microbes. Our approach identified genes in glycolysis and glyoxylate pathway as top predictors of synergy and antagonism respectively. Our systems approach enables tailoring of antibiotic therapies based on the pathogen microenvironment.

https://www.ncbi.nlm.nih.gov/pubmed/30596642