ArticleACS chemical biology2013
Identification of novel inhibitors of nonreplicating Mycobacterium tuberculosis using a carbon starvation model.
Article in ACS chemical biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed, 86 citations in OpenAlex.
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- TowardMicroorganisms · 2024Review
- Molecular and microbiological methods for the identification of nonreplicating Mycobacterium tuberculosis.PLoS pathogens · 2024Review
- Structures of the Mycobacterium tuberculosis efflux pump EfpA reveal the mechanisms of transport and inhibition.Nature communications · 2024Article
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- Structures of the essential efflux pump EfpA fromResearch square · 2024Article
- Benzene Amide Ether Scaffold is Active against Non-replicating and IntracellularACS infectious diseases · 2023Article
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- Characterization of spectinamide 1599 efficacy against different mycobacterial phenotypes.Tuberculosis (Edinburgh, Scotland) · 2023Article
- Identification of 2-Amino Benzothiazoles with Bactericidal Activity against Mycobacterium tuberculosis.Microbiology spectrum · 2023Article
- SigH stress response mediates killing of Mycobacterium tuberculosis by activating nitronaphthofuran prodrugs via induction of Mrx2 expression.Nucleic acids research · 2023Article
- Advances in the design of combination therapies for the treatment of tuberculosis.Expert opinion on drug discovery · 2023Review
- Anti-tuberculosis treatment strategies and drug development: challenges and priorities.Nature reviews. Microbiology · 2022Review
- Tools to develop antibiotic combinations that target drug tolerance inFrontiers in cellular and infection microbiology · 2022Review
- Evolution of Antibacterial Drug Screening Methods: Current Prospects for Mycobacteria.Microorganisms · 2021Review
- Determining Minimum Inhibitory Concentrations in Liquid Cultures or on Solid Medium.Methods in molecular biology (Clifton, N.J.) · 2021Article
- A Multistress Model for High Throughput Screening Against Nonreplicating Mycobacterium tuberculosis.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Mycobacterial drug discovery.RSC medicinal chemistry · 2020Review
- Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era.Frontiers in microbiology · 2020Review
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
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.
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