Quantitative Design of Multi-drug Regiments for Tuberculosis

描述（由申请人提供）：结核病，由结核分枝杆菌感染引起，仍然是对全球健康的严重威胁。结核分枝杆菌潜伏感染世界上三分之一的人，每年造成数百万人死亡。结核病的治疗仍然很困难。药物治疗方案包括四种抗生素和至少六个月的治疗。虽然抗生素治疗可以迅速杀死相当一部分细菌，但有些细胞能够耐受长时间的治疗，因此需要长时间的药物暴露。艰苦的治疗使得依从性和治愈困难，导致耐药菌株的传播和出现。因此，我们迫切需要设计更短、更有效的结核病治疗方法。结核病的基本治疗几十年来没有显著改善。这一失败部分是由于缺乏对耐药亚群特征的了解。在这里，我们试图克服这一障碍，通过表征这些重要的亚群，并使用定量描述他们的生理和抗生素治疗的反应，合理地设计改进的药物治疗方案。我们最近开发了一种基于微流体的活细胞显微镜系统，用于研究单个分枝杆菌的生长特性和抗生素反应。使用我们的系统，我们发现一种不寻常的单极生长模式会导致分枝杆菌的生长速度和抗生素敏感性发生变化。我们认为这种不对称生长模式是一种广泛的机制，它产生了具有不同生理特性的细胞亚群，使它们对特定类别的抗生素和宿主诱导的应激具有差异性耐受性。在这里，我们将联合收割机我们的活细胞成像系统与自动图像分析和数学建模，以确定抗生素反应和单个结核分枝杆菌细胞的细胞生长和细胞周期特征之间的关系。我们将合并线性回归模型与新的半机械药效学模型，将单细胞描述转化为群体行为。我们将使用我们的模型和实验系统来设计和测试新的给药方案，有效地针对药物和免疫耐受分枝杆菌亚群的产生和生存。我们预计，这项研究将提供一个基础框架，以系统地设计改进的临床结核病治疗，同时也建立了一个广泛适用的方法，合理地设计改进的其他疾病的治疗。

DESCRIPTION (provided by applicant): Tuberculosis, caused by infection with Mycobacterium tuberculosis, remains a serious threat to global health. Mycobacterium tuberculosis latently infects a third of the world and kills millions every year. Treating tuberculosis remains difficult. The drug regimen involves four antibiotics and a minimum of six months of treatment. Though antibiotic treatment kills a significant portion of the bacterial population quickly, some cells are able to tolerate treatment for extended periods of time and therefore necessitate the long drug exposure. The arduous treatment makes compliance and cure difficult, leading to transmission and emergence of drug tolerant strains. We therefore have a dire need to design shorter, more effective treatments against tuberculosis. The basic treatment for tuberculosis has not been significantly improved in decades. This failure is due, in part, to a lack of understanding of the features of drug tolerant subpopulations. Here, we seek to overcome this obstacle by characterizing these important subpopulations and using quantitative descriptions of their physiology and response to antibiotic treatment to rationally design improved drug regimens. We have recently developed a microfluidics-based live cell microscopy system to study the growth properties and antibiotic response of individual mycobacteria. Using our system, we discovered that an unusual pattern of unipolar growth creates variability in the growth rate and antibiotic susceptibility of mycobacteria. We propose that this pattern of asymmetric growth is a broad mechanism that creates subpopulations of cells with distinct physiological properties that make them differentially tolerant to specific classes of antibiotics and host induced stress. Here, we will combine our live-cell imaging system with automatic image analysis and mathematical modeling to determine the relationship between antibiotic response and the cell growth and cell cycle characteristics of individual Mycobacterium tuberculosis cells. We will merge linear regression models with novel semi-mechanistic pharmacodynamic models that translate single cell descriptions into population behavior. We will use our models and experimental system to design and test new dosing schedules that effectively target the generation and survival of drug- and immune-tolerant mycobacterial subpopulations. We anticipate that this study will provide a foundational framework to systematically engineer improved clinical tuberculosis treatments while also establishing a broadly applicable methodology to rationally design improved therapies for other diseases.