Effects of Host Metabolic Variation on Antibiotic Susceptibility

宿主代谢变化对抗生素敏感性的影响

• 批准号: 10088499
• 负责人: Jason Hung-Ying Yang
• 金额: $ 24.9万
• 依托单位: RBHS-NEW JERSEY MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-20 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10088499
• 关键词: Adjuvant; Advisory Committees; Affect; Antibiotic Resistance; Antibiotic Therapy; Antibiotic susceptibility; Antibiotics; Award; Bacteria; Biochemical Pathway; Biology; C57BL/6 Mouse; Carbon; Cells; Cessation of life; Chemicals; Clinical; Clinical Management; Clinical Treatment; Communicable Diseases; Culture Media; Data; Development; Dimensions; Disease Resistance; Environment; Escherichia coli; Formulation; Future; Germ-Free; Goals; Growth; Human; Immunity; In Vitro; Infection; Innovative Therapy; International; Investigation; Knock-out; Knowledge; Light; Liquid substance; Machine Learning; Measures; Mentors; Mentorship; Metabolic; Metabolic Pathway; Metabolism; Mission; Modeling; Mus; Nitrogen; Outcome; Pathogenicity; Pathway interactions; Patient-Focused Outcomes; Peritoneal; Peritoneal Fluid; Peritoneal lavage; Phase; Phosphorus; Plasma; Predisposition; Process; Public Health; Publishing; Recovery; Research; Research Training; Sampling; Serum; Site; Source; Sulfur; Supplementation; System; Systems Biology; Testing; Training; Treatment outcome; United States National Institutes of Health; Variant; Virulence; Work; bacterial metabolism; bactericide; base; biological adaptation to stress; career; clinical practice; cohort; commensal microbes; counterscreen; desensitization; genome-wide; improved; in vivo; infectious disease treatment; insight; metabolome; metabolomics; microbial; novel therapeutics; overexpression; pathogen; pathogenic bacteria; precision medicine; programs; public health relevance; respiratory; response; skills; tool; treatment strategy

 DESCRIPTION (provided by applicant): Host variation affects the pathogenicity of, susceptibility to, and recovery from infectious diseases. Elucidating how the host environment alters antibiotic susceptibility is therefore a critical step towards the long-term goal of realizig precision medicine for the clinical management of infectious diseases. The overall objective of this project is to identify the metabolic pathways participating in antibiotic susceptibility and t determine how host metabolism may affect antibiotic treatments at the site of infection. The working hypothesis is that metabolic processes can function as bacterial control mechanisms for antibiotic susceptibility and that the host metabolome can act on these processes to affect the outcome of antibiotic treatment. This hypothesis will be tested in three specific aims: (1) identif metabolic pathways involved in antibiotic susceptibility (K99 phase); (2) characterize changes in the host metabolome elicited by antibiotic administration (K99 phase); (3) evaluate effects of the host metabolome on antibiotic killing (R00 phase). During the mentored K99 phase, bactericidal antibiotics will be counterscreened with various metabolites to identify metabolic perturbations that can affect antibiotic susceptibility. Metabolic pathways contributing to antibiotic lethality ill be identified by combining this data with metabolic modeling and machine learning. Additionally, plasma and peritoneal fluid will be sampled and metabolomically profiled from a mouse peritoneal infection model, with and without antibiotic treatment. These profiles will be used to determine if antibiotics can alter the host metabolism in ways that may affect antibiotic susceptibility at the site of infection. During the independent R00 phase, the effects of host metabolic variation on antibiotic killing will be systematically tested by quantifying antibiotic susceptibility in synthesized media defined by metabolomic profiles from published and measured human and mouse plasma samples. A better understanding of how the host metabolic environment participates in antibiotic treatment fits NIH's public health mission and has direct implications for the clinical management of infectious diseases. Work from the proposed studies will form a quantitative framework for directly evaluating how host metabolism may affect antibiotic treatment outcomes and guide improved antibiotic stewardship in clinical practice. Although the applicant has significant expertise in systems biology, this award will provide the applicant research training to gain new experimental skills and an opportunity for continued career training and mentorship from an advisory committee comprised of international leaders in systems biology, metabolomics, chemical biology and infectious diseases. The support and training provided by this award and by the advisory committee will provide the applicant tools and expertise critical to his future independent research program.

 描述（由适用提供）：宿主变化影响感染疾病的致病性，易感性和恢复性的致病性。因此，阐明宿主环境如何改变抗生素的敏感性是朝着迈向抗生素易感性的关键一步，迈出了对传染病的临床管理的长期目标。该项目的总体目的是确定参与抗生素易感性的代谢途径，并确定宿主代谢如何影响感染部位的抗生素治疗方法。工作假设是，代谢过程可以充当抗生素易感性的细菌控制机制，并且宿主代谢组可以对这些过程作用以影响抗生素治疗的结果。该假设将以三个特定的目的进行检验：（1）确定与抗生素易感性有关的代谢途径（K99期）； （2）表征抗生素给药（K99期）引起的宿主代谢的变化； （3）评估宿主代谢对抗生素杀伤的影响（R00期）。在Mendored K99期间，将用各种代谢物对细菌抗生素进行筛选，以鉴定可能影响抗生素易感性的代谢扰动。通过将这些数据与代谢建模和机器学习相结合，可以确定导致抗生素致死性的代谢途径。此外，将从小鼠腹膜感染模型中取样血浆和腹膜液，并进行抗生素治疗的代谢。这些特征将用于确定抗生素是否可以通过影响感染部位的抗生素易感性的方式改变宿主代谢。在独立的R00阶段，将通过量化由已发表和测量的人和小鼠血浆样品定义的合成培养基中的抗生素易感性来系统地测试宿主代谢变异对抗生素杀戮的影响。更好地了解宿主代谢环境如何参与抗生素治疗，这符合NIH的公共卫生任务，并直接对传染病的临床管理产生影响。拟议研究的工作将构成一个定量框架，用于直接评估宿主代谢如何影响抗生素治疗结果，并指导改善临床实践中的抗生素管理。尽管申请人在系统生物学方面拥有重要的专家，但该奖项将为申请人研究培训提供新的实验技能，并从咨询委员会持续的职业培训和心态的机会完成了系统生物学，代谢组学，化学生物学和感染性疾病的国际领导者。该奖项和咨询委员会提供的支持和培训将为他的未来独立研究计划至关重要的申请人工具和专业知识。