Towards the Translation of Synergistic Phage-Polymyxin Combination Therapy against Pandrug-resistant Klebsiella pneumoniae: A Systems Approach

针对泛耐药肺炎克雷伯菌的协同噬菌体-多粘菌素联合疗法的转化：系统方法

• 批准号: 10470088
• 负责人: Jian Li
• 金额: $ 13.72万
• 依托单位: MONASH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-16 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10470088
• 关键词: Address; Affect; Amino Acids; Animals; Antibiotic Resistance; Antibiotic Therapy; Antibiotics; Antimicrobial Resistance; Attention; Bacteria; Bacterial Infections; Bacteriophages; Biology; Cells; Citrates; Clinic; Clinical; Clinical Trials; Combined Antibiotics; Combined Modality Therapy; Complex; Critical Illness; Cytolysis; Dangerousness; Diagnostic; Dose; Drug Kinetics; Future; Health; Human; Immune; Immune response; Immunocompromised Host; In Vitro; Infection; Innovative Therapy; Klebsiella pneumoniae; Knowledge; Life; Literature; Lytic; Mediating; Medical; Membrane Lipids; Metabolism; Modeling; Multi-Drug Resistance; Multiomic Data; Mus; National Institute of Allergy and Infectious Disease; Nucleotides; Outcome; Patients; Pentosephosphate Pathway; Pharmacodynamics; Pharmacology; Plasmids; Play; Polymyxin B; Polymyxin Resistance; Polymyxins; Regimen; Reporting; Research; Resistance; Resistance development; Resort; Role; Safety; Security; Site; Specificity; Superbug; System; Therapeutic; Time; Toxic effect; Translations; Virus; World Health Organization; bacterial metabolism; bacterial resistance; carbapenem resistance; combat; dosage; global health; in vivo; innovation; metabolomics; multidisciplinary; multiple omics; novel; novel therapeutics; pathogen; priority pathogen; programs; rational design; resistance mechanism; resistant Klebsiella pneumoniae; synergism; virtual

Antimicrobial resistance (AMR) has become one of the greatest global threats to human health. Pandrug- resistant (PDR) Klebsiella pneumoniae has been identified by the World Health Organization as one of the 3 top- priority pathogens urgently requiring new treatments. Polymyxins are often used as the last option; however, plasmid-mediated polymyxin resistance highlights the urgency to develop novel therapeutics to treat PDR K. pneumoniae. Bacteriophage (i.e. phage) has recently attracted substantial attention as a promising option to treat PDR bacterial infections; unfortunately, resistance to phage monotherapy in K. pneumoniae can rapidly develop. Optimal phage-antibiotic combinations provide a superior approach; however, there is a significant lack of knowledge on the pharmacokinetics/pharmacodynamics/toxicodynamics (PK/PD/TD) of phage therapy. This situation has severely hindered the optimization of phage therapy against bacterial ‘superbugs’ and limited their clinical utility. Traditional PK/PD/TD plays a critical role in optimizing antibiotic dosage regimens, but lacks systems and mechanistic information. Furthermore, antibiotic PK/PD/TD cannot be easily extrapolated to phage therapy, mainly due to their unique PK, host specificity and self-amplification. As phage-antibiotic synergy also depends on the dynamics of infection and host responses, innovative strategies incorporating systems pharmacology and host-pathogen-phage-antibiotic interactions have the significant potential to optimize their clinical use. Excitingly, we have isolated a number of phages with superior activity against PDR K. pneumoniae, and identified several novel phage-antibiotic combinations (e.g. with polymyxins) that synergistically kill PDR K. pneumoniae in vitro and in animals without any regrowth. Considering the urgent need to optimize phage therapy and minimize resistance to the last-line polymyxins, it is essential to develop superior phage-polymyxin combinations using a systems approach by integrating PK/PD/TD and multi-omics. Therefore, the Specific Aims of this application are: (1) To identify superior synergistic combinations of phage and polymyxin B, and evaluate their PK/PD/TD against PDR K. pneumoniae using in vitro and animal infection models; (2) To elucidate the mechanisms of synergistic bacterial killing by the superior phage-polymyxin combinations and the host- pathogen-phage-polymyxin interactions using correlative multi-omics; and (3) To develop novel QSP models integrating PK/PD/TD and multi-omics data for the superior phage-polymyxin combinations targeting PDR K. pneumoniae, and propose optimal dosage regimens for future clinical trials. Our innovative multi-disciplinary project will generate urgently needed information for rational optimization of novel phage-polymyxin combinations. Importantly, this proposal aligns perfectly with the present NIAID RFA for exploiting phages to kill ‘superbugs’ and responds in a timely manner to the recent 2019 NIAID Antibiotic Resistance Framework to protect global health security.

抗菌素耐药性（AMR）已成为全球人类健康面临的最大威胁之一。潘德鲁格- 耐药（PDR）肺炎克雷伯菌已被世界卫生组织确定为三大耐药菌之一。 迫切需要新疗法的优先病原体。多粘菌素通常用作最后的选择；然而， 质粒介导的多粘菌素耐药性凸显了开发新疗法来治疗 PDR K 的紧迫性。 肺炎杆菌。噬菌体（即噬菌体）最近作为一种有前途的选择引起了广泛关注 治疗 PDR 细菌感染；不幸的是，肺炎克雷伯菌对噬菌体单一疗法的耐药性可以迅速 发展。最佳噬菌体-抗生素组合提供了一种更好的方法；然而，还存在重大不足 噬菌体疗法的药代动力学/药效学/毒效动力学（PK/PD/TD）知识。这 这种情况严重阻碍了针对细菌“超级细菌”的噬菌体疗法的优化，并限制了它们的应用 临床实用性。传统的 PK/PD/TD 在优化抗生素剂量方案中发挥着关键作用，但缺乏 系统和机械信息。此外，抗生素 PK/PD/TD 不能轻易外推至噬菌体 疗法，主要由于其独特的PK、宿主特异性和自我放大。由于噬菌体-抗生素的协同作用 取决于感染的动态和宿主反应，结合系统的创新策略 药理学和宿主-病原体-噬菌体-抗生素相互作用具有优化其作用的巨大潜力 临床使用。令人兴奋的是，我们分离出了许多对 PDR 肺炎克雷伯菌具有优异活性的噬菌体， 并鉴定了几种新型噬菌体-抗生素组合（例如与多粘菌素）可协同杀死 PDR K。 肺炎链球菌在体外和动物体内没有任何再生。考虑到优化噬菌体疗法的迫切需要 并最大限度地减少对最后一线多粘菌素的耐药性，开发优质噬菌体多粘菌素至关重要 通过集成 PK/PD/TD 和多组学，使用系统方法进行组合。因此，具体目标 本申请的目的是： (1) 鉴定噬菌体和多粘菌素 B 的优异协同组合，并评估 使用体外和动物感染模型针对 PDR 肺炎克雷伯菌的 PK/PD/TD； (2) 阐明 优越的噬菌体-多粘菌素组合和宿主协同杀死细菌的机制 使用相关多组学研究病原体-噬菌体-多粘菌素相互作用； (3) 开发新颖的 QSP 模型 整合 PK/PD/TD 和多组学数据，获得针对 PDR K 的优质噬菌体-多粘菌素组合。 肺炎链球菌，并为未来的临床试验提出最佳剂量方案。我们的创新多学科 该项目将为新型噬菌体多粘菌素的合理优化产生急需的信息 组合。重要的是，该提案与目前的 NIAID RFA 完全一致，即利用噬菌体杀死病毒 “超级细菌”并及时响应最近的 2019 年 NIAID 抗生素耐药性框架 保护全球卫生安全。

项目成果

Comparative metabolomics revealed key pathways associated with the synergistic killing of multidrug-resistant Klebsiella pneumoniae by a bacteriophage-polymyxin combination.

比较代谢组学揭示了与通过噬菌体 - polymyxin组合通过协同杀死多药耐药性肺炎肺炎的关键途径。

• DOI: 10.1016/j.csbj.2021.12.039
• 发表时间: 2022
• 期刊: Computational and structural biotechnology journal
• 影响因子: 6
• 作者: Han ML;Nang SC;Lin YW;Zhu Y;Yu HH;Wickremasinghe H;Barlow CK;Creek DJ;Crawford S;Rao G;Dai C;Barr JJ;Chan K;Turner Schooley R;Velkov T;Li J
• 通讯作者: Li J