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

2015年，活动性结核病(TB)病例为1040万例，因以下原因死亡140万例 结核病。虽然我们有有效的结核病治疗，但耐药病例的发生率正在增加， 威胁到结核病控制的努力。2015年，48万新的耐多药结核病(MDR-TB)病例 都被报道过。其中，近6万人为广泛耐药结核病(XDR-TB)。这个 在一些地区，情况要糟糕得多。在白俄罗斯，每两个病例中就有近一个(48%)是 耐多药结核病(35.3%的新发患者和76.5%的既往治疗患者)。由于全球治愈率 耐多药结核病的发病率仍远低于世卫组织为2015年设定的目标(在许多地区 世界)，由于广泛耐药结核病的治疗成功率更低(白俄罗斯为20%)， 迫切需要更好地了解问题并确定/评估新的 毒品/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定位的药物贝达奎兰， 在世界卫生组织的资助下，利奈唑胺、氯法齐明和地拉曼德正在进行中 本组织和全球基金。作为这两项试验的一部分，每月的痰样本将 从所有患者身上收集了六个月的数据。不幸的是，在对30名患者进行的第一次试验中 完成联合治疗后，6例治疗失败，1例死亡 已经被记录下来了。该项目旨在利用两个试验创造的资源，以便 为了揭示以前未知的耐药机制，耐药的进化途径， 以及对这四种新药/改变用途的药物的抗药性时间表。我们的方法将用于 电子比较基因组和表观遗传学(甲基组和转录组)分析 对失败治疗中的非特征性(表观)基因组变化进行全面的分类 案子。在与基因和调节元件相关的基因和调控元件的电子功能表征中 对这五种研究药物的抗药性将阐明抗药性的机制。后续的 对时间进程样本的系统基因组分析和MIC特征将使我们能够 了解抗药性的进化路径，以及每次抗药性后抗药性水平的变化 进化事件。这将使我们能够了解，例如，在 步数不断增加，或自发地处于较高水平。对于前者，我们将被 能够识别与每种抗性相关的逐步遗传和甲基化标记 水平。这允许临床医生决定是增加药物剂量还是改变 药物疗法是最好的治疗方法。

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.