Axcella Health, Cambridge, Massachusetts, United States of America.
Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.
PLoS Comput Biol. 2018 Dec 31;14(12):e1006677. doi: 10.1371/journal.pcbi.1006677. eCollection 2018 Dec.
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.
抗生素需要在体内的各种环境中有效。然而，病原体微环境会对抗生素的效力产生重大影响。此外，抗生素越来越多地被联合使用以对抗耐药性，但微环境对药物组合疗效的影响尚不清楚。为了详尽地探讨不同微环境对药物组合的影响，我们在这里开发了一个计算框架——基于代谢和基因组的抗生素方案定制（MAGENTA）。MAGENTA 使用个体药物的化学生态基因组特征和代谢扰动来预测不同微环境中协同或拮抗的药物相互作用。我们通过搜索 72 种药物的 2556 种药物组合，在 9 种不同的环境中发现了对大肠杆菌和鲍曼不动杆菌具有强大协同作用的抗生素组合。MAGENTA 还准确预测了在甘油培养基中生长时抑菌和杀菌药物组合疗效的变化，我们在这两种微生物中都通过实验证实了这一点。我们的方法确定了糖酵解和乙醛酸途径中的基因分别是协同作用和拮抗作用的最佳预测因子。我们的系统方法能够根据病原体微环境定制抗生素治疗方案。
