CRISPR Interference Predicts Synergistic Drug Targets in the Mycobacterial Folate Biosynthesis Pathway

Abstract

Multidrug therapies are commonly used in treating infections such as tuberculosis and leprosy, as the expected treatment effectiveness of using synergistic drug combinations is higher than that of using separate drugs combined. Conventional synergistic drug targets prediction methods screen gene knock-out bacterial mutants with antibiotic drugs to identify gene targets responsible for increased susceptibility. However, this prediction method is often unreliable and yields false-positive results. Here, we showed that transcriptional repression-inducing CRISPR interference (CRISPRi) may be a more reliable tool for identifying synergistic drug targets in the genus Mycobacterium. In the model organism M. smegmatis mc2155, we first knocked down gene transcription in the folate biosynthesis pathway and assessed M. smegmatis susceptibility to trimethoprim (TMP), an established drug that treats certain mycobacterial infections by targeting the folA gene product. We found that M. smegmatis showed increased susceptibility to TMP after knocking down folP, folK, and thyX separately, but not pabB. Afterwards, we designed a duplexed CRISPRi method by simultaneously knocking down the transcription of gene pairs, and then assessed the growth inhibitory effect. We discovered that growth was only inhibited when the knocked-down gene pairs are folP/folA or folP/folK, but not folP/pabB or folK/pabB. Our work supported previous research that folP and folA are synergistic targets because they are in the same metabolic loop of the pathway, whereas pabB and folA are not. This implies CRISPRi’s potential to help further characterize why certain drug targets are synergistic, which may be answered by building a CRISPRi-based, multi-gene knock-down library in mycobacteria.