Project 3: Tolerance of Viral/Bacterial Co-infections

项目3：病毒/细菌混合感染的耐受性

• 批准号: 8813147
• 负责人: Amanda M Jamieson
• 金额: $ 28.44万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8813147
• 关键词: 5 year old; Bacterial Infections; Bacterial Pneumonia; Bioinformatics; Biology; Cause of Death; Cell Line; Cell Survival; Cells; Centers of Research Excellence; Cessation of life; Child; Clinical; Communicable Diseases; Complex; Complication; Computational Biology; Databases; Epithelial Cells; Gene Expression; Gene Expression Profile; Genes; Hospitalization; Human; Immune response; In Vitro; Infection; Inflammatory; Legionella pneumophila; Life; Lung; Lung diseases; Maps; Modeling; Molecular Profiling; Morbidity - disease rate; Mouse Cell Line; Mus; Organism; Pathway interactions; Pharmaceutical Preparations; Pneumonia; Publications; Research; Resistance; Sum; System; Testing; Treatment Protocols; Viral; antimicrobial; big biomedical data; co-infection; combat; direct application; human disease; in vivo; in vivo Model; influenzavirus; microbial; mortality; mouse model; novel; pandemic disease; pathogen; productivity loss; resistance factors; resistance mechanism; respiratory infection virus; response; seasonal influenza; small molecule; tissue repair; transcriptome sequencing

ABSTRACT While infection biology has largely focused on studying the immune response to a single infection it is becoming increasingly clear that many infections involve more than one pathogen. Therefore studying the effect of one pathogen on the response to another is of utmost clinical importance. Infection with the seasonal influenza virus leads to an estimated 500,000 deaths annually and during global pandemics these numbers are even higher. Bacterial pneumonia is a common complication following infection with influenza virus, which leads to increased morbidity and mortality (1). We propose that the ability to survive an infection is determined by two main factors, resistance (the ability to respond to and clear the pathogen) and tolerance (the ability to tolerate the effects of a given pathogen burden) (2). Myself and others have shown that infection with influenza virus compromises a variety of resistance mechanisms to many different bacterial pathogens. However, in a recent publication I have shown that during influenza virus/bacterial coinfection tolerance is also compromised (3). In a mouse model of influenza virus/Legionella pneumophila coinfection the pathogen load remained unchanged allowing us to focus on tolerance mechanisms. We found that by decreasing the inflammatory immune response and increasing the tissue repair response we were able to increase tolerance to coinfection. As these complex infections are very difficult to treat effectively this finding opens up a new avenue of research and potential treatments for human infectious disease. In this current study we will use a bioinformatics approach to explore the transcriptional profiles of coinfected lungs and lung epithelial cells by RNA-Seq (Aim1). We will use these transcriptional profiles to find and screen small molecule drugs (perturbagens) that increase tolerance to coinfection in an in vitro system (Aim2). We will then apply these findings to increasing tolerance in our in vivo model (Aim3). This study will allow us to discover novel mechanisms of tolerance and treatments viral/bacterial coinfections of the lung. This project has direct applications to human diseases. With the increase in organisms that are resistant to common antimicrobials new treatment regimens are necessary to combat infectious diseases. In addition, even with effective antimicrobial treatments damage can be caused that decreases tolerance, and we must focus on both treating the host and targeting the microbial pathogens. This is particularly true in the context of complex polymicrobial coinfections. Ultimately these findings can be applied to tolerance mechanisms of other lung diseases.

抽象的 虽然感染生物学主要集中于研究对单一感染的免疫反应，但 越来越清楚，许多感染涉及多种病原体。因此研究 一种病原体对另一种反应的影响至关重要。季节性感染 流感病毒每年导致大约500,000人死亡，在全球大流行期间，这些数字是 更高。细菌性肺炎是感染流感病毒后常见的并发症， 导致发病率和死亡率增加（1）。我们建议确定感染的能力 通过两个主要因素，抗药性（对病原体的反应和清除）和公差（能够 容忍给定病原体负担的影响）（2）。我和他人表明流感感染 病毒损害了许多不同细菌病原体的多种抗性机制。但是，在一个 最近的出版物我已经表明，在流感病毒/细菌共感染耐受性期间也受到损害 （3）。在流感病毒/军团肺肺同伴的小鼠模型中，病原体负荷保持 不变的使我们能够专注于容忍机制。我们发现通过减少炎症 免疫反应并增加了组织修复反应，我们能够提高共同感染的耐受性。 由于这些复杂的感染非常难以有效治疗，因此这一发现开辟了新的研究途径 以及人类传染病的潜在治疗方法。在本研究中，我们将使用生物信息学 通过RNA-Seq（AIM1），探索共感染肺和肺上皮细胞的转录谱的方法。 我们将使用这些转录轮廓来查找和筛选增加的小分子药物（扰动药） 在体外系统中共同感染的耐受性（AIM2）。然后，我们将将这些发现应用于增加的公差 我们的体内模型（AIM3）。这项研究将使我们能够发现耐受性和治疗的新型机制 肺的病毒/细菌共感染。该项目直接应用于人类疾病。与 抗性抗菌药物具有抗性新治疗方案的生物体增加是必要的 战斗传染病。此外，即使有效的抗菌治疗损害也可能造成 这降低了公差，我们必须专注于治疗宿主和靶向微生物病原体。 在复杂的多生物共感染的背景下，尤其如此。最终这些发现可能是 应用于其他肺部疾病的耐受机制。