Identification of novel inhibitors of nonreplicating Mycobacterium tuberculosis using a carbon starvation model

利用碳饥饿模型鉴定非复制型结核分枝杆菌的新型抑制剂

阅读:1

Abstract

During 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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。