Discovering the mechanism of action of novel antibacterial agents through transcriptional profiling of conditional mutants.

We present a new strategy for predicting novel antibiotic mechanisms of action based on the analysis of whole-genome microarray data. We first built up a reference compendium of Bacillus subtilis expression profiles induced by 14 different antibiotics. This data set was expanded by adding expression profiles from mutants that showed downregulation of genes coding for proven or emerging antibacterial targets. Here, we investigate conditional mutants underexpressing ileS, pheST, fabF, and accDA, each of which is essential for growth. Our proof-of-principle analyses reveal that conditional mutants can be used to mimic chemical inhibition of the corresponding gene products. Moreover, we show that a statistical data analysis combined with thorough pathway and regulon analysis can pinpoint the molecular target of uncharacterized antibiotics. We apply this approach to two novel antibiotics: a recently published phenyl-thiazolylurea derivative and the natural product moiramide B. Our results support recent findings suggesting that the phenyl-thiazolylurea derivative is a novel phenylalanyl-tRNA synthetase inhibitor. Finally, we propose a completely novel antibiotic mechanism of action for moiramide B based on inhibition of the bacterial acetyl coenzyme A carboxylase.