Integrated modeling of Klebsiella pneumoniae infections based on bacterial genotype, patient factors and colonization status

摘要 肺炎克雷伯菌是美国医院获得性感染的主要原因，在美国 常见碳青霉烯类耐药肠杆菌科细菌与超广谱β-内酰胺酶 物种。感染Cre可导致高达50%的败血症死亡率，而ESBL和Cre感染都是一种 发病率过高和住院费用过高的重要原因。我们对1765名患者的初步数据表明 肺炎克雷伯菌胃肠道定植患者继发疾病的风险很高(优势比 P&lt；0.0001)，并感染它们的定植菌株。抗生素疗法可以挽救生命，但 选择正确的方案需要在发病几天后获得抗菌药敏感性数据 疾病。殖民测试可以为干预提供一个理想的机会：医生可以在- 风险患者，并使用他们定植菌株的抗生素敏感性数据来做出合理的选择 经验式疗法。高危患者可以作为干预的目标，但患者之间的复杂互动 而细菌因素导致疾病的原因尚不清楚。为了缩小这一知识差距，我们已经组建了多个 由内科科学家、流行病学家、生物信息学家和具有以下专业知识的统计学家组成的学科团队 临床微生物学、微生物发病机制和传染病。这项建议的目的是 确定细菌和宿主因素，预测肺炎克雷伯菌在殖民地患者中的感染。我们的中央 假设肺炎克雷伯菌菌株的毒力潜力不同，而K。 肺炎的基因型别和宿主的易感性决定了定植患者的患病风险。为了测试这一点 假设，我们验证了一种名为致病相关基因座的新的基因组比较方法 用测序(PAL-Seq)方法鉴定肺炎克雷伯菌与肺炎克雷伯菌相关的可变区基因 感染。我们还建立了肺炎克雷伯菌感染患者危险因素的初步临床模型。我们 将通过以下具体目标检验我们的假设并达到这一提议的目标：目标1： 确定在殖民地患者中肺炎克雷伯菌感染的患者危险因素。我们将使用电子医疗 来自三家医院的队列中的记录和培养样本，以建立和验证基于患者的模型 特征和定植密度作为定植患者感染的危险因素，并在 ESBL亚群和CRE亚群定植患者。目标2：识别预测风险的肺炎克雷伯菌基因 在殖民地病人中的疾病。使用定植和侵袭性分离株，我们将应用我们的PAL-Seq管道来 确定与感染相关的细菌基因，在动物模型和独立队列中验证它们， 并在ESBL和CRE定植患者中测试候选毒力基因。这项工作的积极影响将 要立竿见影，要实实在在。我们将迅速提高对肺炎克雷伯菌发病机制的认识。 基于临床和动物研究，并开发可用于识别高风险的预测模型 预防或快速治疗肺炎克雷伯菌感染的高危患者。

Abstract Klebsiella pneumoniae is a leading cause of hospital-acquired infections in the United States and the most common Carbapenem-resistant Enterobacteriaceae (CRE) and Extended-Spectrum Beta-lactamase (ESBL) species. Infections with CRE cause up to 50% mortality from sepsis, and both ESBL and CRE infections are a significant cause of excess morbidity and hospital costs. Our preliminary data from 1765 patients indicates that patients with K. pneumoniae gastrointestinal colonization are at a high risk of subsequent disease (Odds ratio 4.0; p<0.0001) and become infected with their colonizing strain. Antibiotic therapy can be life-saving but choosing the correct regimen requires antimicrobial susceptibility data that is available days after the onset of disease. Testing for colonization could provide an ideal opportunity for intervention: physicians can identify at- risk patients and use antibiotic susceptibility data from their colonizing strain to make rational choices for empiric therapy. High-risk patients could be targeted for intervention, but how the complex interaction of patient and bacterial factors leads to disease is unknown. To close this gap in knowledge, we have assembled a multi- disciplinary team of physician-scientists, epidemiologists, bioinformaticians, and statisticians with expertise in clinical microbiology, microbial pathogenesis and infectious diseases. The objective of this proposal is to identify the bacterial and host factors that predict K. pneumoniae infections in colonized patients. Our central hypothesis is that K. pneumoniae strains vary in their virulence potential, and the combination of K. pneumoniae genotype and host susceptibility determines the risk of disease in a colonized patient. To test this hypothesis, we validated a novel genome comparison method called Pathogenicity-Associated Loci sequencing (PAL-Seq) to identify K. pneumoniae genes in variable genomic regions that are associated with infection. We also developed a preliminary clinical model of patient risk factors for K. pneumoniae infection. We will test our hypothesis and meet the objective of this proposal through the following specific aims: Aim 1: Define patient risk factors for K. pneumoniae infection in colonized patients. We will use electronic medical records and culture samples in cohorts from three hospitals to build and validate models based on patient characteristics and colonization density as risk factors for infection in colonized patients, and test the models in the subgroup of ESBL and CRE colonized patients. Aim 2: Identify K. pneumoniae genes that predict the risk of disease in colonized patients. Using colonizing and invasive isolates, we will apply our PAL-Seq pipeline to identify bacterial genes associated with infection, validate them in animal models and an independent cohort, and test candidate virulence genes in ESBL and CRE colonized patients. The positive impact of this work will be immediate and substantial. We will rapidly advance our understanding of K. pneumoniae pathogenesis based on both clinical and animal studies, and develop predictive models that could be used to identify high- risk patients for prevention or rapid treatment of K. pneumoniae infection.