Accelerating early antituberculosis drug discovery by creating mycobacterial indicator strains that predict mode of action

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.