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

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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.