Systems Immunolobiology of Antibiotic-Persistent MRSA Infection

 描述(申请人提供)：金黄色葡萄球菌菌血症(SAB)是一种常见的危及生命的血液感染，通常由耐甲氧西林菌株(MRSA)引起。令人迫切关注的是，高达30%的SAB患者未能通过抗生素治疗，即使使用了黄金标准的抗MRSA治疗(万古霉素[VAN]或达托霉素(DAP))。这些患者有持续性的菌血症，这往往会导致令人沮丧的临床结果。尽管这些患者的MRSA分离株基于体外CLSI断裂点似乎对VAN或DAP“敏感”，但这些抗生素无法清除血液感染。这种体内的抗生素耐药性被称为抗生素持久性MRSA菌血症，简称APMB。目前，这些危及生命的感染几乎没有治疗选择。有一个关键的，尚未得到满足的需要，以了解推动APMB的宿主和病原体因素的独特交集。阐明这些因素有望导致新的方法来前瞻性地识别有发展为APMB的风险的患者，以及预防或治疗这种通常具有破坏性的感染的新策略。重要的是，APMB代表了抗生素耐药感染的一个独特的子集，它不同于生物膜相关的感染，这是由于“耐药”或 “顽固不化/复发”分离株。APMB分离株是遗传稳定的，但通过体内抗生素暴露诱导的高度适应性菌株。因此，持续性感染机制(APMB)不同于抗生素耐药感染。基于我们大量的初步数据，我们假设APMB是病原体、宿主免疫反应和抗生素三者相互作用的结果。我们进一步认为，研究这一临床重要现象的传统方法可能不足以理解它。因此，我们将：1)分析野生型和突变型APMB菌株与宿主细胞和成分在体外、体外和鉴别动物模型中的相互作用，以解决驱动APMB的金黄色葡萄球菌持续存在的关键基因和表型决定因素；2)利用我们开创性的金黄色葡萄球菌菌血症组(SABG)人类样本和匹配临床分离株的生物储存库，基因组和转录分析，以及免疫表型分析，确定在VAN或DAP治疗期间APMB的宿主遗传和免疫特征；3)使用我们强大的基于系统的统计和计算免疫学方法来整合高通量基因组学和跨研究的转录组数据的结果，以模拟APMB特有的病原体-宿主特征。因此，我们将解决驱动APMB的病原体和宿主因素，使创新方法能够预测、预防和治疗MRSA血流感染，尽管使用抗生素治疗，这些感染仍然存在。这些迫切需要的进展将来自研究的迭代改进，这些研究汇集了一支杰出研究团队的已被证明的优势，以应用一种综合的、基于系统的方法。这一结果将产生稳健的预测算法，用于改进对MRSA感染的干预措施的临床评估。因此，通过为协同而优化的前沿方法和战略，我们在这个U01项目中逐渐集中的研究理想地响应了美国国立卫生研究院和这一“抗菌素耐药性系统生物学”RFA(RFA-AI-14-064)的优先事项。

 DESCRIPTION (provided by applicant): Staphylococcus aureus bacteremia (SAB) is a common and life-threatening bloodstream infection that is often caused by methicillin-resistant strains (MRSA). Of urgent concern, up to 30% of SAB patients fail antibiotic treatment even when gold-standard anti-MRSA therapy (vancomycin [VAN] or daptomycin (DAP]) is used. These patients have persistent bacteremia, which frequently results in a dismal clinical outcome. Even though the MRSA isolates from these patients appear to be "susceptible" to VAN or DAP based upon in vitro CLSI breakpoints, these antibiotics fail to clear the bloodstream infection. Such in vivo antibiotic resistance is termed Antibiotic-Persistent MRSA Bacteremia, or APMB. At present, there are few therapeutic options for these life-threatening infections. There is a critical, unmet need to understand the unique intersection of host and pathogen factors driving APMB. Elucidating these factors holds promise to lead to new approaches to prospectively identify patients at risk for developing APMB, and novel strategies to prevent or treat this often devastating infection. Importantly, APMB represents a unique subset of antibiotic resistant infections that differ from biofilm-associated infections due to "antibiotic-tolerant" or "recalcitrant / relapsing" isolates. APMB isolates are genetically stable, but highly adaptive strains induced by in vivo antibiotic exposure. Thus, mechanisms of persistent infections (APMB) are distinct from antibiotic-tolerant infections. Based on our extensive preliminary data, we hypothesize that APMB results from a three-way interaction among the pathogen, host immune response and antibiotic. We further posit that conventional approaches to study this clinically important phenomenon may be insufficient to understand it. Therefore, we will: 1) analyze the interactions of wild-type and mutant APMB strains with host cells and constituents in vitro, ex vivo, and in discriminative animal models to resolve key genotypic & phenotypic determinants of the S. aureus persistome that drives APMB; 2) leverage our pioneering S. aureus Bacteremia Group (SABG) biorepository of human samples & matched clinical isolates, genomic & transcriptional analysis, and immunophenotyping to define host genetic and immune profiles of APMB during VAN or DAP treatment; and 3) use our powerful systems-based statistical and computational immunology approaches to integrate results of high-throughput genomics and transcriptomics data across studies to model the pathogen-host signatures unique to APMB. Therefore, we will resolve the pathogen and host factors that drive APMB to enable innovative approaches to predict, prevent and treat MRSA bloodstream infections that persist despite antibiotic treatment. These critically needed advances will derive from iterative refinement of studies that bring together proven strengths of an outstanding research team to apply an integrated, systems-based approach. The result will yield robust predictive algorithms for clinical evaluation for improved interventions against MRSA infections. Thus, through leading-edge methods and strategies that are optimized for synergy, our progressively focused studies in this U01 project are ideally responsive to the priorities of the NIH and this "Systems Biology of Antibacterial Resistance" RFA (RFA-AI-14-064).