P011

Mycobacterium tuberculosis, which causes human tuberculosis, is amongst the world’s deadliest pathogens. Increasing rates of drug resistance pose challenges for treatment and control, which must be addressed by discovering new drugs with new targets. Conventional target prioritisation focuses only on gene products essential for bacterial survival are targeted, but recently a spectrum of vulnerability was revealed. In polyploid organisms, this recessivity of loss-of-function is caused by the topology of genetic interactions. This topology also determines pathways to resistance in response to inhibitors of a given target by imposing constraints on evolution. To better understand the essentiality spectrum in M. tuberculosis and anticipate resistance, we aim to map genetic interdependencies and define gene-gene interactions essential for mycobacterial survival. We developed a dual CRISPRi/dCas9 system to independently titrate transcription of thousands of gene pairs in M. tuberculosis in parallel and measure the resulting fitness phenotypes using targeted next-generation sequencing. Alongside understanding the genetic network topology of M. tuberculosis, the resulting gene-gene interactions will comprise a reference dataset to assist interpretation of data from PROSPECT, a large-scale chemical-genetic interaction screening platform, to prioritise small molecules with new targets towards developing therapies with reduced selective pressures.