An efficient CRISPR interference-based prediction method for synergistic/additive effects of novel combinations of anti-tuberculosis drugs

Tuberculosis (TB) is treated by chemotherapy with multiple anti-TB drugs for a long period, spanning 6 months even in a standard course. In perspective, to prevent the emergence of antimicrobial resistance, novel drugs that act synergistically or additively in combination with major anti-TB drugs and, if possible, shorten the duration of TB therapy are needed. However, their combinatorial effect cannot be predicted until the lead identification phase of the drug development. Clustered regularly interspaced short palindromic repeats interference (CRISPRi) is a powerful genetic tool that enables high-throughput screening of novel drug targets. The development of anti-TB drugs promises to be accelerated by CRISPRi. This study determined whether CRISPRi could be applicable for predictive screening of the combinatorial effect between major anti-TB drugs and an inhibitor of a novel target. In the checkerboard assay, isoniazid killed 
 
 Mycobacterium smegmatis
 
 synergistically or additively in combinations with rifampicin or ethambutol, respectively. The susceptibility to rifampicin and ethambutol was increased by knockdown of inhA, which encodes a target molecule of isoniazid. Additionally, knockdown of rpoB, which encodes a target molecule of rifampicin, increased the susceptibility to isoniazid and ethambutol, which act synergistically with rifampicin in the checkerboard assay. Moreover, CRISPRi could successfully predict the synergistic action of cyclomarin A, a novel TB drug candidate, with isoniazid or rifampicin. These results demonstrate that CRISPRi is a useful tool not only for drug target exploration but also for screening the combinatorial effects of novel combinations of anti-TB drugs. This study provides a rationale for anti-TB drug development using CRISPRi.