Multi Omics Data Integration to predict the M. tuberculosis Bedaquiline Resistance Phenotype from the Genotype

Drug resistance is caused by DNA mutations in certain Mycobacterium tuberculosis genes, which in turn modify or effect
drug targeted proteins (enzymes) directly or indirectly. Currently, clinical research on the best combinations in which to use new drugs
suffers from a genotype-phenotype gap: we can test for resistance in the lab (phenotype) but we can’t predict the phenotype from
mutations. Resistance testing for Bedaquiline is even more complex than for other TB drugs, further widening this gap. Most Bedaquiline
resistance appears to result from mutations in a non-essential gene, Rv0678, which regulates an efflux pump, rather than mutations in the
Bedaquiline target gene, atpE, which is part of the M. tuberculosis respiratory chain. This ‘indirect’ efflux pump mediated resistance is
complicated by a wide range of mutations in Rv0678, some of which appear to paradoxically confer hyper-susceptibility. This genotype-phenotype
gap can be narrowed by applying advanced novel computational methods for integration of data from multiple (holistic)
data (called omics data integration). We propose to test the hypothesis that genomic mutations in Rv0678 result in changes in
gene transcription, which patterns can predict the level of phenotypic Bedaquiline resistance, also of previously unseen mutations. These
findings, if our hypothesis is correct, will form the basis for diagnostic tests that allow assigning correct treatment to patients suffering from
drug resistant tuberculosis.