CRISPR Interference-based Screening for Prediction of Synergistic/Additive Effects of Novel Combinations of Anti-Tuberculosis Drugs

Abstract

Tuberculosis (TB) patients must receive treatment for a long period, spanning at least 6 months. In some cases, this long period of treatment leads to inappropriate administration of anti-TB drugs and cessation of TB therapy, a hotbed of antimicrobial resistance. From this perspective, novel drugs that act synergistically or additively in combination with major anti-TB drugs are required to shorten the duration of TB therapy. Clustered regularly interspaced short palindromic repeats interference (CRISPRi) is a powerful genetic tool which is expected to accelerate the development of TB drugs. In this study, we investigated whether CRISPRi could be used for predictive screening of the combined effect of anti-TB drugs. Knockdown of inhA, a target molecule of isoniazid (INH), increased susceptibility to rifampicin (RFP) and ethambutol, which act synergistically or additively with INH. This phenomenon was also true in the case of knockdown of rpoB, a target molecule of RFP. Moreover, CRISPRi could successfully predict the synergistic action of cyclomarin A with INH or RFP. These results demonstrate that CRISPRi is a helpful tool not only for exploring drug targets, but also for screening the combinatorial effects of known anti-TB drugs. This study provides evidence of CRISPRi platform-based anti-TB drug development.