TY - JOUR
T1 - Genetic determinants of drug resistance in Mycobacterium tuberculosis and their diagnostic value
AU - Farhat, Maha R.
AU - Sultana, Razvan
AU - Iartchouk, Oleg
AU - Bozeman, Sam
AU - Galagan, James
AU - Sisk, Peter
AU - Stolte, Christian
AU - Nebenzahl-Guimaraes, Hanna
AU - Jacobson, Karen
AU - Sloutsky, Alexander
AU - Kaur, Devinder
AU - Posey, James
AU - Kreiswirth, Barry N.
AU - Kurepina, Natalia
AU - Rigouts, Leen
AU - Streicher, Elizabeth M.
AU - Victor, Tommie C.
AU - Warren, Robin M.
AU - van Soolingen, Dick
AU - Murray, Megan
N1 - FTX; (CC BY)
PY - 2016
Y1 - 2016
N2 - Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs.Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance.Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and predidtion tool.Measurements and Main Results: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci.Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.
AB - Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs.Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance.Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and predidtion tool.Measurements and Main Results: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci.Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.
KW - multidrug-resistant tuberculosis
KW - molecular diagnostics
KW - sensitivity and specificity
KW - GENOTYPE MTBDRSL TEST
KW - ANTIBIOTIC-RESISTANCE
KW - COMPLEX STRAINS
KW - EPIDEMIOLOGY
KW - PYRAZINAMIDE
KW - MUTATIONS
KW - 2ND-LINE
KW - TOOL
KW - FLUOROQUINOLONES
KW - CLASSIFICATION
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000382416100018
U2 - 10.1164/rccm.201510-2091OC
DO - 10.1164/rccm.201510-2091OC
M3 - A1: Web of Science-article
SN - 1073-449X
VL - 194
SP - 621
EP - 630
JO - American Journal of Respiratory and Critical Care Medicine
JF - American Journal of Respiratory and Critical Care Medicine
IS - 5
ER -