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Project 2: Response to Treatment

项目 2：治疗反应

基本信息

批准号：
10339374
负责人：
DAVID R SHERMAN
金额：
$ 74.61万
依托单位：
SEATTLE CHILDREN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-02-12 至 2024-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10339374
关键词：
Acids Adherence Adopted Antibiotics Bacteria Cell Separation Cessation of life Cholesterol Clinical Data Disease Drug Exposure Drug Modelings Drug Tolerance Drug resistance Drug resistance in tuberculosis Exhibits Exposure to Genetic Genetic Screening Genetic Transcription Goals Human Hypoxia In Vitro Individual Infection Infectious Agent Knowledge Link Maps Metabolic Microscopy Modeling Mus Mycobacterium tuberculosis Outcome Persons Pharmaceutical Preparations Pharmacotherapy Phase Phenotype Physiological Prediction of Response to Therapy Proteins Regimen Regulation Relapse Research Rifampin Risk Series Solid System Testing Time Toxic effect Treatment Failure Treatment outcome Validation base chemotherapy clinical predictors design drug action drug development drug discovery drug-sensitive experimental study global health human disease improved in vivo individual variation insight isoniazid metabolomics molecular modeling multiple omics network models novel response transcriptomics treatment response treatment strategy tuberculosis drugs

项目摘要

Abstract – Project 2 The responses of Mtb to individual drugs and regimens and their relationship to treatment outcome remains variable and poorly understood. Our premise is that knowledge of bacterial networks and their regulatory controls constitute a powerful but underexplored window to novel targets and treatment strategies. The major goal of this project is to identify strain-independent and strain-specific cellular networks associated with varying drug responses in Mtb, and their regulation. In Aim 1 this project will utilize carefully selected clinical drug-sensitive Mtb isolates exhibiting varying responses to treatment to characterize the genetic, transcriptional, and metabolic differences revealed by exposure to important anti-TB drugs, and then to map those changes to condition-specific drug tolerance phenotypes. We will subject each strain to detailed analyses including transcriptomics, metabolomics, and regulator-based genetic screens in response to front line antibiotics and in conditions that promote tolerance. In Aim 2 we will employ the data from Aim 1 to build and refine regulatory network models that elucidate both common and strain-specific Mtb strategies to subvert drug action. These models will be refined by testing model driven predictions through an iterative series of multi-omic analyses and perturbations including more focused experiments such as targeted protein interaction studies, bacterial cell sorting and solid-phase time-lapse microscopy. Ultimately, in Aim 3 we will test the extent to which the drug-response network models generated in Aims 1 and 2 predict clinical treatment outcomes, and identify potential strategies to interfere with adaptive drug-response network states to improve the efficacy of chemotherapy. We will further test the relevance of identified drug response networks in targeted studies of Mtb isolates from treatment failures in humans. The outcome of this project will be the identification and validation of the specific cellular networks associated with varying drug responses in Mtb and their regulation.

摘要-项目2 结核分枝杆菌对个别药物和治疗方案的反应及其与治疗结果的关系仍然存在变量和知之甚少。我们的前提是了解细菌网络及其调控机制，对照构成了新靶点和治疗策略的一个强有力但未充分探索的窗口。该项目的主要目标是确定与细胞网络相关的菌株独立和菌株特异性。在结核分枝杆菌中具有不同的药物反应，以及它们的调节。在目标1中，该项目将利用精心挑选的临床药物敏感性Mtb分离株对治疗表现出不同的反应，通过暴露于重要的抗结核药物揭示的转录和代谢差异，然后绘制这些变化对特定条件的药物耐受性表型。我们将对每种菌株进行详细的包括转录组学、代谢组学和基于调节子的基因筛选在内的分析，线抗生素和条件，促进耐受性。在目标2中，我们将使用目标1的数据，建立和完善监管网络模型，阐明共同和菌株特异性结核病战略，颠覆毒品行动这些模型将通过迭代测试模型驱动的预测来完善，一系列多组学分析和扰动，包括更有针对性的实验，如靶向蛋白质相互作用研究、细菌细胞分选和固相延时显微镜。最终，在Aim 3 我们将测试在目标1和2中生成的药物反应网络模型预测临床疗效的程度。治疗结果，并确定干扰适应性药物反应网络状态的潜在策略来提高化疗的效果。我们将进一步检验已确定药物反应的相关性在针对人类治疗失败的结核分枝杆菌分离株的靶向研究中，该项目的成果将是识别和验证与不同药物相关的特定细胞网络，结核分枝杆菌的反应及其调控。