Novel strategies to detect and eliminate persistent Mycobacterium tuberculosis - applications in a murine Cornell model

结核病是一种可治愈的疾病，但仍然是世界上最大的杀手之一。它每年在全世界造成近200万人死亡，98%的结核病死亡发生在发展中国家，主要影响处于生产年龄的年轻人。25万结核病死亡者也感染了削弱人体免疫系统的艾滋病毒，其中大多数人在非洲。结核病尤其影响到最脆弱的人群，包括儿童、最贫穷者和营养不良者。结核病是由一种叫做结核分枝杆菌的细菌引起的。这种疾病的一个重要特征是细菌具有在人体内生长和存活很长时间的不寻常能力。因此，据估计，20亿人，相当于世界总人口的三分之一，感染了这种细菌，它在其中引起不明显的潜伏感染，引起5-10%的活动性结核病的终生风险。这些持久存在的细菌不能用标准的微生物方法培养，也不能被目前的结核病药物杀死。因此，肺结核治疗至少需要6个月的时间，用4种药物才能治愈患者。这种长期治疗极其难以实施，特别是在发展中国家，因为患者和医疗保健服务都负担不起，基础设施有限。使用有效的结核病药物缩短治疗时间是很重要的，因为这将大大减少病人的痛苦、副作用和病人及其家属的费用。此外，较短的结核病治疗时间可使患者早日恢复生产活动。这项研究旨在确定和量化结核病感染小鼠在新药治疗前和治疗期间的持久性细菌，以预测结核病治疗的结果。通过添加复苏促进因子（RPF），这些复苏促进因子是由M.结核病重新开始生长。我们在最近的研究中表明，在小鼠中存在依赖RPF生长的持久性细菌。在目前的治疗药物方案中加入大剂量利福平，能够杀死依赖于RPF的持久细菌，因此，缩短了治疗时间，没有疾病复发。这意味着，如果我们能够从患者中去除RPF依赖性细菌，治疗时间可以缩短，复发率降低。在这项提案中，我们将应用我们从使用一套新型药物方案研究小鼠中学到的相同原理和技术来预测人类结核病治疗的结果，特别是疾病复发。我们将在小鼠中建立一个模型系统，作为一个试验床，以评估新药物方案的效力，然后再将其用于更昂贵和耗时的人体试验。

Tuberculosis is a curable disease but still remains one of the biggest killers in the world. It kills nearly 2 million people worldwide every year and 98% of tuberculosis deaths are in the developing world affecting mostly young adults in their productive years. A quarter of a million tuberculosis deaths are also infected with HIV which weakens human immune systems, most of these people are in Africa. Tuberculosis especially affects the most vulnerable populations including children, the poorest and malnourished. Tuberculosis is caused by the bacterium called Mycobacterium tuberculosis. One important characteristics of this disease is that the bacterium has an unusual ability to grow and survive for extended periods of time in human body. Therefore, it has been estimated that 2 billion people, equal to one third of the world's total population, are infected with the bacterium in whom it causes unnoticeable latent infection that gives rise to a 5-10% lifetime risk of active tuberculosis. These persistent bacteria cannot be cultured using standard microbiological methods and are not killed by the current tuberculosis drugs. Therefore, tuberculosis treatment needs at least 6 months with four drugs to cure the patients. This long-term treatment is extremely difficult to implement especially in developing countries because of lack of affordability in both patients and healthcare services and limited infrastructure. It is important that treatment duration is shortened using effective tuberculosis drugs as it will significantly reduce patient suffering, side effect and expenses incurred by both patients and their families. In addition, shorter TB treatment duration may allow an earlier return of patients to their productive activities. The proposed research aims to identify and quantify those persistent bacteria in tuberculosis infected mice before and during treatment with new drugs to predict the outcome of tuberculosis treatment. The persistent bacteria will be "woken" by the addition of resuscitation promoting factors (RPFs) which are proteins produced by M. tuberculosis to restart growth. We have shown in our recent study that in mice there were persistent bacteria which depended on RPFs to grow. High-dose rifampicin which was added in the current treatment drug regimen was able to kill RPF-dependent persistent bacteria, as a result, treatment was cut short with no disease relapse. This meant that if we are able to remove RPF-dependent bacteria from patents, the treatment duration could be shortened with reduced relapse rate. In this proposal, we will apply the same principals and techniques which we have learnt from studying mice using a set of novel drug regimens to predict the outcome of human tuberculosis treatment, especially disease relapse. We will set up a model system in mice as a test bed to evaluate the potencies of new drug regimens before usage of them in much more expensive and time-consuming human testing.