Team:Peking

Project Description

Tuberculosis, caused by Mycobacterium tuberculosis, remains one of the world's most serious public health problems. Although tuberculosis is curable and the treatment success rate is high, it is still the second most common cause of death from infectious disease (after HIV). It causes more than 1.3 million deaths annually, and most of the deaths occur in developing countries that are lack of effective identification of those in need of therapy, with an enormous amount of delayed or failed diagnosis.


Case detection is currently the rate-limiting step in disease control. The available Nucleic Acid Detection (NAD) Method is sensitive and fast, but does not reach the requirement of specificity and reliability.


To obviate such problems, Peking iGEM team is developing a novel PC Reporters system that can transform biomarkers of the disease into optical signal. Combined with array design and statistical analysis, the presence of Mycobacterium tuberculosis can be easily verified. It can also be easily used in developing areas with designed hardware development. We believe this new advanced system can turn out as a powerful tool in disease diagnosis, with high specificity and reliability.

Awards
Best New Composite Part
Best Part Collection

Poster
97 - Zone 4 - Hall C
Presentation
9/26/2015 - Room 302 - 11:30 AM

Thanks for your attention!

Specificity

A nucleic-acid-based, sequence-specific detection system named "paired dCas9" (PC) reporter was built. Its specificity and sensitivity proved to be enough to detect real MTB genome.

Reliability

An array of MTB-specific markers was designed to use information from the entire genome of MTB to improve the reliability of diagnosis. By statistics, we are able to present the readouts in a quantitative way.

Portability

Noticing that most TB cases occur in developing areas, we built an electronic device that was portable, affordable, and easy to use.

Bench to Bedside

Coming from bedside to bench, we set out to apply our bench achievements back to bedside. With consultation, survey and feedback from clinical practice, we are still working on improving our detection system!