Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, USA.
Department of Bioengineering, Innovative Genomics Institute, University of California, Berkeley, CA, USA.
Mol Syst Biol. 2022 Jan;18(1):e10495. doi: 10.15252/msb.202110495.
Understanding mechanisms of antibiotic failure is foundational to combating the growing threat of multidrug-resistant bacteria. Prodrugs-which are converted into a pharmacologically active compound after administration-represent a growing class of therapeutics for treating bacterial infections but are understudied in the context of antibiotic failure. We hypothesize that strategies that rely on pathogen-specific pathways for prodrug conversion are susceptible to competing rates of prodrug activation and bacterial replication, which could lead to treatment escape and failure. Here, we construct a mathematical model of prodrug kinetics to predict rate-dependent conditions under which bacteria escape prodrug treatment. From this model, we derive a dimensionless parameter we call the Bacterial Advantage Heuristic (BAH) that predicts the transition between prodrug escape and successful treatment across a range of time scales (1-10 h), bacterial carrying capacities (5 × 10 -10 CFU/µl), and Michaelis constants (K = 0.747-7.47 mM). To verify these predictions in vitro, we use two models of bacteria-prodrug competition: (i) an antimicrobial peptide hairpin that is enzymatically activated by bacterial surface proteases and (ii) a thiomaltose-conjugated trimethoprim that is internalized by bacterial maltodextrin transporters and hydrolyzed by free thiols. We observe that prodrug failure occurs at BAH values above the same critical threshold predicted by the model. Furthermore, we demonstrate two examples of how failing prodrugs can be rescued by decreasing the BAH below the critical threshold via (i) substrate design and (ii) nutrient control. We envision such dimensionless parameters serving as supportive pharmacokinetic quantities that guide the design and administration of prodrug therapeutics.
了解抗生素失效的机制是对抗日益严重的多药耐药菌威胁的基础。前药-在给药后转化为具有药理活性的化合物-代表了一类用于治疗细菌感染的治疗方法,但在抗生素失效的情况下研究较少。我们假设依赖病原体特异性途径将前药转化为治疗方法的策略容易受到前药激活和细菌复制的竞争速率的影响,这可能导致治疗逃逸和失败。在这里,我们构建了一个前药动力学的数学模型,以预测细菌逃避前药治疗的速率依赖性条件。从这个模型中,我们得出了一个无量纲参数,我们称之为细菌优势启发式(BAH),该参数预测了在一系列时间尺度(1-10 小时)、细菌承载能力(5×10 -10 CFU/µl)和米氏常数(K = 0.747-7.47 mM)范围内,前药逃避和成功治疗之间的转变。为了在体外验证这些预测,我们使用了两种细菌-前药竞争模型:(i)一种抗菌肽发夹,它被细菌表面蛋白酶酶促激活;(ii)一种与硫麦芽糖结合的三甲氧嘧啶,它被细菌麦芽糖转运蛋白内化,并被游离巯基水解。我们观察到,在前药失败的情况下,BAH 值高于模型预测的相同临界阈值。此外,我们通过(i)底物设计和(ii)营养控制,展示了两种使失效的前药通过将 BAH 值降低到临界阈值以下来恢复的示例。我们设想这种无量纲参数可以作为支持性药代动力学参数,指导前药治疗药物的设计和管理。