Strategies for improving the efficacy of combinatorial antibiotic therapy in chronic infections

提高慢性感染联合抗生素治疗疗效的策略

• 批准号: 10736285
• 负责人: Catherine Ann Wakeman
• 金额: $ 34.67万
• 依托单位: TEXAS TECH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-11 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10736285
• 关键词: Antibiotic Resistance; Antibiotic Therapy; Antibiotic susceptibility; Antibiotics; Automobile Driving; Bacterial Infections; Caring; Cell physiology; Cells; Cessation of life; Chemicals; Chronic; Clinical; Clinical Microbiology; Clinical Treatment; Combined Antibiotics; Communicable Diseases; Communities; Complex; Complex Mixtures; DNA cassette; Data; Development; Environment; Evolution; Exhibits; Failure; Future; Gene Exchanges; Horizontal Gene Transfer; Human; Infection; Intelligence; Knowledge; Laboratories; Life Expectancy; Lung; Lung infections; Medical; Methodology; Microbe; Modeling; Modern Medicine; Mutation; Nature; Pharmaceutical Preparations; Physiological; Physiology; Predisposition; Publishing; Research; Research Project Grants; Resistance; Site; Source; Testing; Therapeutic; Treatment Failure; Wound Infection; antagonist; antibiotic tolerance; antimicrobial drug; antimicrobial tolerance; bacterial community; chronic infection; chronic wound; clinical application; combinatorial; commensal microbes; comorbidity; coping; design; effectiveness evaluation; emerging antibiotic resistance; experience; global health; human morbidity; human mortality; human pathogen; improved; member; microbial; microbial community; microorganism; microorganism interaction; mouse model; novel; pathogen; pathogenic microbe; population health; pressure; resistance mechanism; stressor; synergism; targeted treatment; therapy design; tool; translational potential; treatment strategy; wound

Project Summary/Abstract The spread of antibiotic resistance is a growing concern as the emergence of resistance mechanisms among human pathogens is occurring more rapidly than the development of new antimicrobial agents. This issue contributes to the inability to fully clear persistent infections such as chronic wound and lung infections, which represent a major source of human morbidity and mortality. In turn, the inability to eradicate these persistent infections creates more opportunities for the evolution of novel microbial mechanisms to circumvent therapeutic treatment, exacerbating the problem of antibiotic resistance. There are multiple aspects of the chronic infection environment that contribute to therapeutic failure and the emergence of antibiotic resistance. First, several stressors encountered at the host-pathogen interface are mutagenic, which helps drive evolutionary adaptation in these sites. Second, the polymicrobial nature of many chronic infections can contribute to the spread of resistance mechanisms via horizontal gene transfer. The presence of polymicrobial communities can also further compound the issue of therapeutic clearance of infection since interspecies microbial interactions are known to alter bacterial physiological and lead to antimicrobial tolerance. In this proposal, we seek to target both the microbial evolutionary trajectory at the host-pathogen interface and the polymicrobial nature of chronic infections to design improved therapeutic strategies for eradication of pathogens contributing to otherwise persistent infections. In Aim 1, we propose to target antibiotic resistant isolates through the identification of vulnerability tradeoffs that can occur as the cell shifts its fundamental physiology to cope with antibiotic exposure. In addition to published examples of this phenomenon, we demonstrate our ability to uncover novel examples of tradeoffs that can be exploited to eradicate otherwise recalcitrant microorganisms. We seek to uncover more examples of vulnerability tradeoffs and determine the effectiveness of targeting these tradeoffs in a murine model of chronic wound infection. In Aim 2, we establish polymicrobial community wound pathogen models and use a methodology that we propose can be adapted for use in the clinical laboratory to demonstrate shifts in antibiotic efficacy driven by polymicrobial interactions. We demonstrate that both polymicrobial synergism (a reduction in antibiotic efficacy in complex bacterial communities) and polymicrobial antagonism (an increase in antibiotic efficacy in the context of a polymicrobial consortium) can be readily observed. Preliminary data suggest that combinatorial treatment strategies can be developed to exploit polymicrobial antagonism to overcome synergistic interactions. We propose to validate this strategy in a murine model of chronic wound infection. Together, these Aims will be used to identify antibiotic treatment strategies that will extend the efficacy of the currently available repertoire of antibiotics.

项目总结/摘要 随着耐药机制的出现， 在人类病原体中的流行比新的抗微生物剂的开发更快。这个问题 导致无法完全清除持续性感染，如慢性伤口和肺部感染， 是人类发病率和死亡率的主要来源。反过来，无法根除这些持续存在的 感染为新的微生物机制的进化创造了更多的机会， 治疗，加剧了抗生素耐药性的问题。慢性感染有多个方面 环境，导致治疗失败和抗生素耐药性的出现。首先，几个 在宿主-病原体界面遇到的压力是诱变性的，这有助于推动进化适应 在这些网站上。第二，许多慢性感染的多微生物性质可能有助于 通过水平基因转移的抗性机制。多微生物群落的存在还可以进一步 由于已知种间微生物相互作用 改变细菌生理学并导致抗微生物耐受性。在这一建议中，我们寻求针对 宿主-病原体界面的微生物进化轨迹和慢性感染的多微生物性质 设计改进的治疗策略，以根除病原体， 感染.在目标1中，我们建议通过鉴定脆弱性来靶向抗生素耐药菌株 当细胞改变其基本生理机能以科普抗生素暴露时可能发生的权衡。此外 对于已发表的这一现象的例子，我们展示了我们发现权衡的新例子的能力 可以用来根除其他寄生的微生物。我们试图发现更多的例子 脆弱性权衡，并确定针对这些权衡的有效性，在小鼠模型的慢性 伤口感染在目标2中，我们建立了多微生物群落伤口病原体模型，并使用 我们提出的方法可以适用于临床实验室，以证明抗生素的变化， 由多微生物相互作用驱动的功效。我们证明，多微生物协同作用（减少 复杂细菌群落中的抗生素功效）和多微生物拮抗作用（抗生素 在多微生物聚生体的情况下的功效）可以容易地观察到。初步数据显示， 可以开发组合治疗策略以利用多微生物拮抗作用来克服协同作用 交互.我们建议在慢性伤口感染的小鼠模型中验证这种策略。所有这些 目的将被用来确定抗生素治疗策略，将扩大目前可用的疗效 抗生素的种类