Zhu Yan, Zhao Jinxin, Li Jian
Infection Program and Department of Microbiology, Biomedicine Discovery Institute, Monash University, 19 Innovation Walk, Melbourne, Victoria 3800, Australia.
Eng Microbiol. 2022 Apr 23;2(2):100021. doi: 10.1016/j.engmic.2022.100021. eCollection 2022 Jun.
The increasing antimicrobial resistance has seriously threatened human health worldwide over the last three decades. This severe medical crisis and the dwindling antibiotic discovery pipeline require the development of novel antimicrobial treatments to combat life-threatening infections caused by multidrug-resistant microbial pathogens. However, the detailed mechanisms of action, resistance, and toxicity of many antimicrobials remain uncertain, significantly hampering the development of novel antimicrobials. Genome-scale metabolic model (GSMM) has been increasingly employed to investigate microbial metabolism. In this review, we discuss the latest progress of GSMM in antimicrobial pharmacology, particularly in elucidating the complex interplays of multiple metabolic pathways involved in antimicrobial activity, resistance, and toxicity. We also highlight the emerging areas of GSMM applications in modeling non-metabolic cellular activities (e.g., gene expression), identification of potential drug targets, and integration with machine learning and pharmacokinetic/pharmacodynamic modeling. Overall, GSMM has significant potential in elucidating the critical role of metabolic changes in antimicrobial pharmacology, providing mechanistic insights that will guide the optimization of dosing regimens for the treatment of antimicrobial-resistant infections.
在过去三十年中，日益增长的抗菌药物耐药性已在全球范围内严重威胁人类健康。这一严峻的医学危机以及日益减少的抗生素研发渠道，都需要开发新型抗菌疗法，以对抗由多重耐药微生物病原体引起的危及生命的感染。然而，许多抗菌药物的详细作用机制、耐药性和毒性仍不明确，这严重阻碍了新型抗菌药物的研发。基因组规模代谢模型（GSMM）已越来越多地用于研究微生物代谢。在本综述中，我们讨论了GSMM在抗菌药理学方面的最新进展，特别是在阐明参与抗菌活性、耐药性和毒性的多种代谢途径的复杂相互作用方面。我们还强调了GSMM在模拟非代谢细胞活动（如基因表达）、识别潜在药物靶点以及与机器学习和药代动力学/药效学建模整合等新兴应用领域。总体而言，GSMM在阐明代谢变化在抗菌药理学中的关键作用方面具有巨大潜力，可为治疗耐药性感染的给药方案优化提供指导机制。
