Modifiable Risk Factors for the Emergence of Resistance to Pseudomonas aeruginosa

项目摘要 耐碳青霉烯类铜绿假单胞菌(CR-P)铜绿假单胞菌)导致大量死亡 住院病人。只有四种β-内酰胺类药物具有抗CR-P的活性。铜绿假单胞菌在美国有售， 其中头孢唑烷-他唑巴坦(C-T)是治疗CR-P最常用的药物。铜绿假单胞菌。临床前 研究表明，C-T对90%的铜绿假单胞菌具有抗菌活性；临床应用后，有报道称P。 最初检测出对C-T敏感，但在治疗过程中产生抗药性的铜绿假单胞菌出现了。 我们的初步数据显示，在连续28名感染CR-P的患者中。铜绿假单胞菌 最初对C-T敏感的菌株，50%的患者随后分离的铜绿假单胞菌具有4倍 C-T暴露后30天，C-T最小抑菌浓度(MIC)升高。我们确认了 通过全基因组测序(WGS)导致抗性的遗传标记-值得注意的是 AmpC-AmpR区和PBP3。令人担忧的是，86%的铜绿假单胞菌最初对另一种细菌敏感 新型抗生素，头孢他啶-阿维巴坦(C-A)，在缺乏C-T暴露的情况下，对C-A表现出抗药性 暴露在C-A中。这是令人担忧的，因为对一种新药物的抗药性的出现可能会消除少数几种 剩下的治疗方案。我们探索了可以降低C-T频率的可修改的风险因素 研究发现，接受C-T治疗超过1小时的患者中，30%的患者随后出现C-T抵抗 而接受药物治疗超过3小时的患者没有出现耐药菌株。我们想要 重复这项探索性工作，并在260名患者中进行实验验证研究 有7家医院将铜绿假单胞菌临床分离株配对保存在-80°C，并开出了C-T处方。 在目标1中，WGS将通过比较配对的CR-P来确定与C-T抗性相关的遗传位点。铜绿假单胞菌 在接触C-T前和接触C-T后30天的同一患者身上分离出的病毒。验证将通过以下方式进行 克隆和定点突变工作。肉汤微量稀释度将决定药敏试验结果 另外三种β-内酰胺类抗生素对CR-P有抗菌活性。以量化铜绿假单胞菌交叉耐药的出现。 在目标2中，我们将利用参与站点的不同C-T管理策略，并制定 机器学习派生决策树，以告知临床医生如何最有效地开出C-T以减少 后天抵抗力的可能性。以下是一些将被调查的潜在风险因素 包括：(1)输注C-T超过3小时，(2)大剂量C-T，(3)联合抗生素治疗，(4)透析 (5)感染源和源头控制，(6)接触C-T的天数。 这项工作将(1)通过高度识别细菌染色体的区域来为未来的药物开发提供信息 容易产生耐药性并需要额外的加固；以及(2)确定可改变的风险因素， 由临床医生使用，使新型抗生素在较长时间内保持有效的治疗选择。

Project Summary Carbapenem-resistant Pseudomonas aeruginosa (CR-P. aeruginosa) contributes to significant mortality in hospitalized patients. Only four β-lactam agents with activity against CR-P. aeruginosa are available in the US, of which ceftolozane-tazobactam (C-T) is the most frequently used to treat CR-P. aeruginosa. Pre-clinical investigations indicate C-T had activity against >90% of P. aeruginosa isolates; after clinical use, reports of P. aeruginosa that initially tested susceptible to C-T but became resistant during therapy emerged. Our preliminary data indicate that amongst 28 consecutive patients infected with CR-P. aeruginosa with isolates initially susceptible to C-T, 50% of patients had subsequent P. aeruginosa isolates with > 4-fold increase in C-T minimum inhibitory concentrations (MICs) up to 30 days after C-T exposure. We identified genetic markers contributing to resistance through whole genome sequencing (WGS) – notably mutations in the ampC-ampR region and in PBP3. Alarmingly, 86% of P. aeruginosa isolates initially susceptible to another novel antibiotic, ceftazidime-avibactam (C-A), exhibited resistance to C-A after C-T exposure - in the absence of C-A exposure. This is concerning as the emergence of resistance to one novel agent could eliminate the few remaining treatment options. We explored modifiable risk factors that could reduce the frequency of C-T resistance and found that 30% of patients who received C-T over 1 hour had subsequent C-T resistant isolates, whereas no patients who received the drug over 3 hours developed resistant isolates. We would like to repeat this exploratory work and include experimental validation studies in a cohort of 260 patients across seven hospitals who have paired P. aeruginosa clinical isolates stored at -80°C and were prescribed C-T. In Aim 1, WGS will identify the genetic loci associated with C-T resistance comparing paired CR-P. aeruginosa isolates from the same patient before and up to 30 days after C-T exposure. Validation will occur through cloning and site-directed mutagenesis work. Broth microdilution will determine susceptibility testing results for the three other β-lactams with activity against CR-P. aeruginosa to quantify the emergence of cross-resistance. In Aim 2, we will capitalize on diverse C-T administration strategies at participating sites and develop a machine learning derived decision tree to inform clinicians how to prescribe C-T most effectively to reduce the likelihood of acquired resistance. The following are some risk factors that will be investigated for potential inclusion: (1) infusion of C-T over 3 hours, (2) high-dose C-T, (3) combination antibiotic therapy, (4) dialysis dependency, (5) source of infection and source control, (6) number of days of C-T exposure. This work will (1) inform future drug development by identifying areas of the bacterial chromosome highly prone to resistance and in need of additional reinforcement and (2) identify modifiable risk factors that can be used by clinicians to enable novel antibiotics to remain effective treatment options for extended periods of time.