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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要随着耐药机制的出现，抗生素耐药性的蔓延日益受到关注人类病原体的传播速度比新抗菌药物的开发速度还要快。本期导致无法完全清除慢性伤口和肺部感染等持续感染，是人类发病率和死亡率的一个主要来源。反过来，又无法根除这些顽固的感染为新型微生物机制的进化创造了更多机会来规避治疗治疗，加剧了抗生素耐药性问题。慢性感染有多个方面导致治疗失败和抗生素耐药性出现的环境。首先，几个在宿主-病原体界面遇到的压力源具有诱变性，这有助于推动进化适应在这些网站中。其次，许多慢性感染的多种微生物性质可能导致疾病的传播通过水平基因转移的耐药机制。多种微生物群落的存在也可以进一步由于已知种间微生物相互作用会导致感染的治疗清除问题变得更加复杂改变细菌生理并导致抗菌药物耐受。在本提案中，我们力求同时针对宿主-病原体界面的微生物进化轨迹和慢性感染的多种微生物性质设计改进的治疗策略来根除导致持久性感染的病原体感染。在目标 1 中，我们建议通过识别脆弱性来针对抗生素耐药菌株当细胞改变其基本生理机能以应对抗生素暴露时，可能会发生权衡。此外通过已发布的这种现象的例子，我们展示了我们发现新的权衡例子的能力可以用来根除顽固的微生物。我们试图发现更多的例子脆弱性权衡，并确定在慢性病小鼠模型中针对这些权衡的有效性伤口感染。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种微生物相互作用驱动的功效。我们证明了多种微生物的协同作用（减少抗生素在复杂细菌群落中的功效）和多种微生物拮抗作用（抗生素的增加）可以很容易地观察到多微生物联合体中的功效。初步数据表明可以开发组合治疗策略来利用多种微生物的拮抗作用来克服协同作用互动。我们建议在慢性伤口感染的小鼠模型中验证这一策略。在一起，这些目标将用于确定抗生素治疗策略，以延长现有药物的疗效抗生素清单。