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Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action [Mycobacterium marinum]

ABSTRACT: Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action [Mycobacterium marinum]

PROVIDER: PRJNA421833 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR6364590_1.fastq.gz	Fastqsanger.gz
	SRR6364590_2.fastq.gz	Fastqsanger.gz
	SRR6364600_1.fastq.gz	Fastqsanger.gz
	SRR6364600_2.fastq.gz	Fastqsanger.gz
	SRR6364610_1.fastq.gz	Fastqsanger.gz

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Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action

Project description:Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action

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Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action [Mycobacterium tuberculosis]

Project description:Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action [Mycobacterium tuberculosis]

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Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action [Mycobacterium marinum]

Project description:Due to the rise of drug resistant forms of tuberculosis there is an urgent need for novel antibiotics to effectively combat these cases and to shorten treatment regimens. Recently, drug screens using whole cell analyses have shown to be successful. However, current high throughput screens focus mostly on stricto sensu life-death screening that give little qualitative information and often require the lengthy process of target and mode of action (MoA) identification. In doing so, promising compound scaffolds or non-optimized compounds that fail to reach inhibitory concentrations are missed. To accelerate early TB drug discovery, we performed RNA sequencing on Mycobacterium tuberculosis and Mycobacterium marinum to map the stress responses that follow upon exposure to sub-inhibitory concentrations of antibiotics with known targets: ciprofloxacin, ethambutol, isoniazid, streptomycin and rifampicin. The resulting dataset comprises the first overview of transcriptional stress responses of mycobacteria to different antibiotics. We show that antibiotics can be distinguished based on their specific transcriptional stress fingerprint i.e. DNA damage for ciprofloxacin and ribosomal stress for streptomycin. Notably, this fingerprint was more distinctive in M. marinum and we decided to use this to our advantage and continue with this model organism. A selection of diverse antibiotic stress genes was used to construct stress reporters. In total, three functional reporters were constructed for DNA damage, cell wall damage and ribosomal inhibition. Subsequently, these reporter strains were used to screen a small anti-TB compound library to predict the mode of action. In doing so we could identify the putative mode of action for three novel compounds, which confirms our approach.

2018-04-12 | GSE107882 | GEO

Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action [Mycobacterium tuberculosis]

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Accelerating early anti-TB drug discovery by creating mycobacterial indicator strains that predict mode of action

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-04-11 | GSE107884 | GEO

Accelerating Early Antituberculosis Drug Discovery by Creating Mycobacterial Indicator Strains That Predict Mode of Action.

Project description:Due to the rise of drug-resistant forms of tuberculosis, there is an urgent need for novel antibiotics to effectively combat these cases and shorten treatment regimens. Recently, drug screens using whole-cell analyses have been shown to be successful. However, current high-throughput screens focus mostly on stricto sensu life/death screening that give little qualitative information. In doing so, promising compound scaffolds or nonoptimized compounds that fail to reach inhibitory concentrations are missed. To accelerate early tuberculosis (TB) drug discovery, we performed RNA sequencing on Mycobacterium tuberculosis and Mycobacterium marinum to map the stress responses that follow upon exposure to subinhibitory concentrations of antibiotics with known targets, ciprofloxacin, ethambutol, isoniazid, streptomycin, and rifampin. The resulting data set comprises the first overview of transcriptional stress responses of mycobacteria to different antibiotics. We show that antibiotics can be distinguished based on their specific transcriptional stress fingerprint. Notably, this fingerprint was more distinctive in M. marinum We decided to use this to our advantage and continue with this model organism. A selection of diverse antibiotic stress genes was used to construct stress reporters. In total, three functional reporters were constructed to respond to DNA damage, cell wall damage, and ribosomal inhibition. Subsequently, these reporter strains were used to screen a small anti-TB compound library to predict the mode of action. In doing so, we identified the putative modes of action for three novel compounds, which confirms the utility of our approach.

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