Difference between revisions of "Team:IISER Pune"
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Revision as of 15:01, 11 September 2015
Welcome to the team page of the Indian Institute of Science Education and Research, Pune's iGEM 2015 site
- Since 6-May-2015 we now have a team of 10 UG members, 2 advisors and one PI!
- We are currently meeting on every alternate day to chalk out our workplan.
- Context of the problem: TB kills more people than most other diseases in the developing world. Diagnostics is either by Zalh-Nielsen staining (1884). Recent advances in PCR have led to DNA based diagnostics. But cost can be a barrier.
Project Description
Tuberculosis, an infectious disease caused by Mycobacterium tuberculosis, affects nearly two billion people all over the world. India has the highest burden of TB with World Health Organisation (WHO) statistics for 2013 giving an estimated incidence of 2.1 million cases of active TB.
M. tuberculosis is a slow growing pathogenic bacterium with a doubling time of approximately 24 hours in tissues. This property of M. tuberculosis hinders rapid detection in sputum samples obtained from patients. The standard stain test does not work for these bacteria as they have a complex mycolic acid layer which prevents uptake of the dyes involved. Although a lot of effort has been focussed on treatment, diagnostics forms the basis of appropriate therapy for drug-sensitive and resistant strains.
Our aim is to leverage synthetic biology to develop a robust and self-sustained genetic device to help rapid diagnostics even in resource poor settings.
Multiple experiments targeting the different components of M. tuberculosis will be performed in an attempt to accelerate the growth of slow growing Mycobacteria. Mathematical modeling and computer simulations will be simultaneously used to model the various parts of the system.
Hence, with a joint approach of experimental testing and modeling, we hope to design a genetic device capable of combining the speed of PCR and the accuracy of microbial culture in the diagnosis of TB.
Therefore, our proposed solution will elegantly reduce the time span for TB diagnosis from days to hours in a cost-effective manner.