Current rapid diagnostic for drug resistant TB detect genetic signatures of M. tuberculosis (MTB) and the mutations that cause drug resistance. Gaps in our knowledge of the mutations that lead to resistance to some first and second line drugs limit the ability of these tools to aid clinicians in choosing effective drug regimens early in the course of disease. The goal of this project is to identify novel mutations that can close the existing gap in the sensitivity of molecular diagnosis of MTB drug resistance, to understand the association between individual and combinations of mutation and quantitative drug resistance and to develop and validate a prediction model that will define the optimal set of mutations to be assessed to improve the performance of rapid molecular diagnostics. In previous work, we have identified over 500 MTB strains for which at least one drug resistance phenotype is unexplained by mutations in the known or suspected resistance genes.
In Aim 1 of this study, we will more precisely define the resistance phenotype by performing MICs and conduct WGS to identify mutations that may encode resistance.
In aim 2, we will expand quantitative resistance phenotyping and perform targeted sequencing of novel drug resistance targets, analyzing these data to determine the impact of individual and interacting mutations on quantitative resistance phenotypes and to develop a model to identify the optimal set of mutations to be included in molecular diagnostics.
In Aim 3, we will validate this model and link it to patient treatment outcomes using a new set of strains that we have prospectively collected in the course of an ongoing NIH-funded longitudinal cohort study in Lima, Peru. Data from this study will inform product development of a proposed micro-array based diagnostic and a study that will perform single point mutagenesis of putative drug resistance determinants and subsequently phenotype the resulting mutants.

Public Health Relevance

The vast majority of MDR TB patients are not diagnosed or treated with appropriate drugs. There is an urgent need for rapid diagnostic tests that enable early diagnosis and the tailoring of drug therapy to drug resistance profiles. The results of this study will provide the basis for adding specific mutations to rapid diagnostic tests like the microarray being developed through this CETR and will result in improving the sensitivity of these early tests for resistance TB.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI109755-05
Application #
9631935
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Parker, Tina M
Project Start
Project End
Budget Start
2018-03-01
Budget End
2019-02-28
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Type
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
Gong, Lingyan; Ouyang, Wei; Li, Zirui et al. (2018) Direct numerical simulation of continuous lithium extraction from high Mg2+/Li+ ratio brines using microfluidic channels with ion concentration polarization. J Memb Sci 556:34-41
Hicks, Nathan D; Yang, Jian; Zhang, Xiaobing et al. (2018) Clinically prevalent mutations in Mycobacterium tuberculosis alter propionate metabolism and mediate multidrug tolerance. Nat Microbiol 3:1032-1042
Linger, Yvonne; Knickerbocker, Christopher; Sipes, David et al. (2018) Genotyping Multidrug-Resistant Mycobacterium tuberculosis from Primary Sputum and Decontaminated Sediment with an Integrated Microfluidic Amplification Microarray Test. J Clin Microbiol 56:
Sakatos, Alexandra; Babunovic, Gregory H; Chase, Michael R et al. (2018) Posttranslational modification of a histone-like protein regulates phenotypic resistance to isoniazid in mycobacteria. Sci Adv 4:eaao1478
Thakore, Nitu; Norville, Ryan; Franke, Molly et al. (2018) Automated TruTip nucleic acid extraction and purification from raw sputum. PLoS One 13:e0199869
Thakore, Nitu; Garber, Steve; Bueno, Arial et al. (2018) A bench-top automated workstation for nucleic acid isolation from clinical sample types. J Microbiol Methods 148:174-180
Ouyang, Wei; Han, Jongyoon; Wang, Wei (2017) Enabling electrical biomolecular detection in high ionic concentrations and enhancement of the detection limit thereof by coupling a nanofluidic crystal with reconfigurable ion concentration polarization. Lab Chip 17:3772-3784
Gong, Lingyan; Ouyang, Wei; Li, Zirui et al. (2017) Force fields of charged particles in micro-nanofluidic preconcentration systems. AIP Adv 7:125020
Yadon, Adam N; Maharaj, Kashmeel; Adamson, John H et al. (2017) A comprehensive characterization of PncA polymorphisms that confer resistance to pyrazinamide. Nat Commun 8:588
Calderón, R I; Velásquez, G E; Becerra, M C et al. (2017) Prevalence of pyrazinamide resistance and Wayne assay performance analysis in a tuberculosis cohort in Lima, Peru. Int J Tuberc Lung Dis 21:894-901

Showing the most recent 10 out of 19 publications