Evolutionary and Functional Significance of Novel Mutations in MDR-XDR TB

耐多药-广泛耐药结核病新突变的进化和功能意义

• 批准号: 9980263
• 负责人: Faramarz Valafar
• 金额: $ 67.07万
• 依托单位: SAN DIEGO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-19 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9980263
• 关键词: Antibiotic Therapy; Antibiotics; Bacillus; Bacteria; Bacteriology; Belarus; Catalogs; Cessation of life; Clinical; Combined Modality Therapy; Communicable Diseases; Contracts; DNA Methylation; DNA sequencing; Drug Combinations; Drug resistance; Epigenetic Process; Event; Evolution; Exposure to; Expression Profiling; Extreme drug resistant tuberculosis; Fluoroquinolones; Funding; Genes; Genetic; Genetic Markers; Genome; Genomics; Goals; Grant; Incidence; Infection; Injectable; Investigation; Laboratories; Lead; Linezolid; Metabolic; Mission; Modeling; Molecular; Multidrug-Resistant Tuberculosis; Mutagenesis; Mutation; Mycobacterium tuberculosis; Patients; Pharmaceutical Preparations; Play; Population; Prevalence; Process; Pyrazinamide; Regimen; Regulatory Element; Reporting; Resistance; Resources; Rifampin; Role; Sampling; Sputum; Testing; Time; TimeLine; Treatment Failure; Treatment Protocols; Treatment outcome; Tuberculosis; Variant; World Health Organization; bacterial resistance; case control; combinatorial; comparative genomics; differential expression; dosage; epigenomics; genome analysis; genome annotation; genome wide association study; genome-wide analysis; improved; in silico; insight; isoniazid; methylation biomarker; methylome; methylomics; network models; novel; novel drug combination; novel therapeutics; pressure; resistance mechanism; response; sample collection; stressor; success; transcriptome; transcriptome sequencing; transcriptomics; tuberculosis drugs; tuberculosis treatment

In 2015, there were 10.4 million cases of active tuberculosis (TB) and 1.4 million deaths due to TB. While we have effective TB treatment, the incidence of drug resistant cases is increasing and threatens TB control efforts. In 2015, 480,000 new cases of multi drug-resistant TB (MDR-TB) were reported. Among these, nearly 60,000 were extensively drug-resistant TB (XDR-TB). The scenario is much worse in some regions. In Belarus, close to one of each two cases (48%) are MDR-TB (35.3% in new and 76.5% in previously treated TB-patients). Since the global cure rate of MDR-TB is still well below the target set by WHO for 2015 (exceedingly low in many parts of the world), and since XDR-TB treatment success rates are even lower (20% in Belarus), there is an urgent need for improved understanding of the problem and to identify/evaluate new drugs/combinations of drugs as the situation in Belarus is likely to spread. Two trials for combinatorial treatment involving four new and repurposed drugs bedaquiline, linezolid, clofazimine, and delamanid are underway thanks to funding from the World Health Organization and the Global Fund. As part of these two trials, monthly sputum samples will be collected for six months from all patients. Unfortunately, in the first trial with 30 patients having completed the combinatorial treatment, in six the treatment has failed, and one death has been recorded. This project aims to leverage the resources created by the two trials in order to uncover previously unknown mechanisms of drug resistance, evolutionary path to resistance, and timeline to resistance to the four new/repurposed drugs. Our approach will be to use in silico comparative genomic and epigenetic (methylome and transcriptomic) analysis in order to curate a comprehensive catalog of uncharacterized (epi)genomic changes in failed treatment cases. In silico functional characterization of genes and regulatory elements associated with resistance to the five study drugs will then elucidate the mechanism of resistance. A subsequent phylogenomic analysis and MIC characterization of time-course samples will allow us to understand the evolutionary path to resistance, and the change in resistance level after each evolutionary event. This will allow us to understand for example whether resistance emerges in steps with increasing levels, or spontaneously at a high level. In the case of the former, we will be able to identify the stepwise genetic and methylation markers associated with each resistance level. This allows the clinician to decide whether increasing the drug dosage or change of the drug regimen is the best course of action.

2015年，有1040万活动性结核病病例，140万人因结核病死亡 结核病。虽然我们有有效的结核病治疗方法，但耐药病例的发生率正在增加， 威胁结核病控制工作。 2015年，耐多药结核病（MDR-TB）新发病例48万例 被报道。其中，近6万例为广泛耐药结核病（XDR-TB）。这 一些地区的情况更糟。在白俄罗斯，近每两个病例中就有一个 (48%) 耐多药结核病（新发结核病患者中为 35.3%，既往治疗过的结核病患者中为 76.5%）。由于全球治愈率 耐多药结核病的发病率仍远低于世界卫生组织设定的 2015 年目标（在许多地区极低） 世界），而且由于广泛耐药结核病治疗成功率甚至更低（白俄罗斯为 20%）， 迫切需要提高对问题的理解并确定/评估新的 药物/药物组合，因为白俄罗斯的情况可能会蔓延。 两项联合治疗试验涉及四种新的和重新利用的药物贝达喹啉， 在世界卫生组织的资助下，利奈唑胺、氯法齐明和德拉马尼正在研发中 组织和全球基金。作为这两项试验的一部分，将每月采集痰样本 从所有患者身上收集了六个月的数据。不幸的是，在 30 名患者的第一次试验中 完成联合治疗后，六人治疗失败，一人死亡 已被记录。该项目旨在利用这两项试验创建的资源，以便 揭示以前未知的耐药机制、耐药性的进化路径， 以及对四种新药/新用途药物产生耐药性的时间表。我们的方法将用于 计算机比较基因组和表观遗传学（甲基化组和转录组）分析，以便 整理失败治疗中未表征的（表观）基因组变化的综合目录 案例。基因和相关调控元件的计算机功能表征 对五种研究药物的耐药性将阐明耐药机制。随后的 时间过程样本的系统基因组分析和 MIC 表征将使我们能够 了解耐药性的进化路径，以及每次耐药后耐药水平的变化 进化事件。例如，这将使我们能够了解阻力是否出现在 逐步增加水平，或自发地达到高水平。对于前者，我们将 能够识别与每种抗性相关的逐步遗传和甲基化标记 等级。这使得临床医生可以决定是否增加药物剂量或改变药物剂量。 药物治疗是最好的治疗方案。