Research Project
10256602
ABSTRACT Chronic lung disease due to non-tuberculous mycobacteria (NTM-LD) is a silent and emerging epidemic in the U.S. and many parts of the world.1-3 The incidence and prevalence of NTM-LD is increasing yearly and now surpasses that of tuberculosis (TB) in the U.S.4 Two of the greatest known risk factors for NTM-LD are chronic obstructive pulmonary disease (COPD) and pre-existing bronchiectasis.3 In the U.S., approximately 12 million individuals have COPD, and it is the third leading cause of death in the U.S.5 In addition, the co-occurrence of bronchiectasis in patients with known COPD is estimated to be up to ~70%.6 Like TB, the requirement for prolonged combination drug therapy is a central tenet of NTM treatment. Consequently, it is essential that several drugs be administered concurrently to maximize sterilizing conditions. Unlike TB for which there are now rapid molecular tests for detection of infection and antimicrobial resistance and recently approved new drugs, diseases caused by NTM are a major concern for multiple reasons, foremost being their intrinsic resistance to most existing antimicrobials in the absence of a rapid diagnostic test for antimicrobial susceptibility or even NTM infection.7,8 Diagnosis of NTM-LD is complicated by the fact that clinical manifestations and radiographic findings for TB and NTM-LD are virtually indistinguishable. Thus, it is important when diagnosing NTM-LD to ?rule out? TB even in regions of lower prevalence, such as the U.S. because of its infectious and deadly nature. To differentiate TB from NTM-LD, clinicians must rely on a combination of mycobacteriology and molecular tests to identify the etiological agent of the disease, which for NTM includes 13 clinically-relevant species/sub-species that must be distinguished from approximately 180 other NTM species that are rarely pathogenic. In addition to the challenge of accurately speciating mycobacteria, there is also the need to detect antibiotic resistance. Hence, the algorithm for mycobacterial diagnostic testing is complex, requiring varied testing methodologies, which are either slow to respond (culture), insensitive (smears), or insufficiently comprehensive (molecular). Molecular detection of respiratory mycobacterial infections and resistance to antibiotics is challenging. The specimen type (sputum) is viscous and highly heterogeneous; the mycobacteria bacilli are difficult to lyse; the number of species is considerable; and the polymorphisms that confer drug resistance are numerous. To address these challenges, we propose to automate and integrate the following into a one user-step test: chaotic mixing of glass beads using a rotating magnetic disc to homogenize sputum and lyse bacilli, a porous disc in a pipette tip to purify and concentrate nucleic acid, and a Lab-on-a-Film test to speciate and detect polymorphisms that confer drug resistance. For Phase 1, we propose to develop a Lab-on-a-Film test that has the required sensitivity to rule in/out TB, diagnose NTM-LD, and detect drug resistance when Mycobacterium tuberculosis (MTB) and/or clinically important NTM are present.
