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Field deployable low cost microfluidic system for real-time isothermal detection of drug resistant tuberculosis

Posted on:2013-03-15Degree:Ph.DType:Dissertation
University:Michigan State UniversityCandidate:Seyrig, Gregoire Francois HenriFull Text:PDF
GTID:1454390008469726Subject:Engineering
Abstract/Summary:
Tuberculosis (TB) caused by Mycobacterium tuberculosis is a global health issue that is responsible for more than 1.6 million deaths annually; majority of which occur in developing nations. In addition to routine TB, often inappropriate use of antibacterial drugs results in multi-drug resistant (MDR) and extensively drug-resistant (XDR) TB strains, which are 500--600 times more expensive to treat. Totally drug-resistant TB is also known. Developing nations often lack the resources to diagnose MDR/XDR TB in time resulting in delayed treatment and further infections. Diagnosis of MDR/XDR TB is challenging because it requires detection of many single nucleotide polymorphisms (SNPs) imparting the resistance. Current strategies for the diagnosis of MDR/XDR TB require expensive instruments costing ∼;Based on optimization studies carried out using 11 fluorescent DNA-intercalating dyes and Bst polymerase, a protocol was developed to detect 10 copies of M. tuberculosis genomic DNA in less than 15 min. Using trehalose, a protocol was established to stabilize molecular biology reagents for their storage at room temperature for up to one year with no or minimal loss of activity. A polyester-based chip that did not contain any valves and allowed multiplex detection without cross contamination between reaction chambers was also developed. An initial proof-of-concept was demonstrated using an SNP associated with isoniazid resistance. Work with patient sputum was outside the scope of this research because of the requirements associated with a BSL3 facility. Overall, this work provides critical data necessary to detect TB, MDR/XDR-TB using a simple platform suitable for limited resource settings.
Keywords/Search Tags:MDR/XDR TB, Detection, Using
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