Transcriptomics

Dataset Information

0

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


ABSTRACT: 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.

ORGANISM(S): Mycobacterium marinum

PROVIDER: GSE107882 | GEO | 2018/04/12

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2018-04-12 | GSE107831 | GEO
2023-03-01 | E-MTAB-12652 | biostudies-arrayexpress
2007-12-25 | GSE9494 | GEO
2015-01-20 | E-GEOD-56749 | biostudies-arrayexpress
2019-08-02 | GSE135236 | GEO
2008-02-12 | GSE10440 | GEO
2020-06-16 | GSE152445 | GEO
2008-02-28 | GSE8953 | GEO
2022-04-15 | GSE193270 | GEO
2024-10-04 | PXD049478 | Pride