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Download fileIdentification of Novel Inhibitors of Nonreplicating Mycobacterium tuberculosis Using a Carbon Starvation Model
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posted on 18.02.2016, 14:46 authored by Sarah
Schmidt Grant, Tomohiko Kawate, Partha
P. Nag, Melanie R. Silvis, Katherine Gordon, Sarah A. Stanley, Edward Kazyanskaya, Raymond Nietupski, Aaron Golas, Michael Fitzgerald, Sanghyun Cho, Scott G. Franzblau, Deborah T. HungDuring Mycobacterium tuberculosis infection, a population
of bacteria is thought to exist in a nonreplicating
state, refractory to antibiotics, which may contribute to the need
for prolonged antibiotic therapy. The identification of inhibitors
of the nonreplicating state provides tools that can be used to probe
this hypothesis and the physiology of this state. The development
of such inhibitors also has the potential to shorten the duration
of antibiotic therapy required. Here we describe the development of
a novel nonreplicating assay amenable to high-throughput chemical
screening coupled with secondary assays that use carbon starvation
as the in vitro model. Together these assays identify
compounds with activity against replicating and nonreplicating M. tuberculosis as well as compounds that inhibit
the transition from nonreplicating to replicating stages of growth.
Using these assays we successfully screened over 300,000 compounds
and identified 786 inhibitors of nonreplicating M.
tuberculosis In order to understand the relationship
among different nonreplicating models, we tested 52 of these molecules
in a hypoxia model, and four different chemical scaffolds in a stochastic
persister model, and a streptomycin-dependent model. We found that
compounds display varying levels of activity in different models for
the nonreplicating state, suggesting important differences in bacterial
physiology between models. Therefore, chemical tools identified in
this assay may be useful for determining the relevance of different
nonreplicating in vitro models to in vivo M. tuberculosis infection. Given our
current limited understanding, molecules that are active across multiple
models may represent more promising candidates for further development.