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Deoxyribozyme sensor-based diagnostics for Mycobacterium tuberculosis

$429,965R15FY2013AINIH

University Of Central Florida, Orlando FL

Investigators

Linked publications, trials & patents

Abstract

DESCRIPTION (provided by applicant): The impact of Mycobacterium tuberculosis (Mtb) on global health is staggering, with ~2 million deaths and ~10 million new cases of tuberculosis (TB) each year. A major contributor to this crisis is the lack of effective point- of-care (POC) diagnostic tools for the detection of active TB disease. This compromises the ability of clinicians to make critical decisions regarding hospitalization, isolation, and treatment. As a result, undiagnosed patients progress to more severe disease and continue to transmit the infection. To make matters worse, efforts to treat TB, which currently involves a 6-9 month multi-drug regimen, are complicated by the increasing incidence of multidrug resistant TB (MDR-TB). Although rapid and accurate drug susceptibility testing (DST) is crucial for the control of active TB, an inexpensive POC diagnostic tool for DST in resource-limited settings is sorely lacking. The goal of this project is to exploit the unique properties of two-component deoxyribozyme (DNAzyme) sensors - high specificity and sensitivity, low cost, feasible implementation in resource-limited settings - to dramatically improve Mtb diagnostic capabilities. In Aim 1, we will design and optimize DNAzyme sensors capable of ultrasensitive, species-specific detection of Mtb RNA directly in sputum samples. In Aim 2, we will apply a similar technology to detect selected single nucleotide polymorphisms (SNPs), mutations that are known to confer resistance to clinically relevant antibiotics. Ultimately, we would seek to combine these two tools to create a novel comprehensive Mtb diagnostic platform. This technology has the potential to significantly improve TB diagnostic capabilities by providing a low-cost, sensitive, and highly specific POC assay that could be implemented in resource limited, high-incidence settings.

View original record on NIH RePORTER →