P29
Combining genotypic, phenotypic and computational structural analysis to characterize the mutations associated with ethionamide resistance in M. tuberculosis clinical isolates
A M Cabibbe(1) P Miotto(1) A Audisio(1) M Chiacchiaretta(1) R Sorrentino(1) F Di Marco(1) A Spitaleri(1) R Provvedi(2) R Manganelli(2) V Mathys(3) D M Cirillo(1)
1:San Raffaele Scientific Institute; 2:University of Padova; 3:Sciensano
The lack of validated mutations to be used as marker of ethionamide (ETH) resistance in M. tuberculosis (MTB) hinders the performance of currently endorsed interpretation catalogues. ETH inhibits the MTB mycolic acid synthesis by targeting FabG1-InhA and is activated by a monooxygenase encoded by the ethA gene. Our study aims at characterizing the effect of ethA mutations on the ETH-R phenotype.
Illumina whole genome sequencing (WGS) and Minimum Inhibitory Concentration (MIC) data on Cryptic plates were collected for 1717 MTB clinical isolates. Genome-wide association analysis (GWAS) was performed between ETH MIC and mutations. The EthA protein was modeled by AlphaFold2 for molecular dynamics simulation and we evaluated the effect of mutations on the protein stability. A subset of ethA mutations was further characterized by allelic exchange.
GWAS identified expected associations with ETH MIC increases (i.e. ethA, fabG1, mshA). We found 194 mutation patterns across the entire ethA gene. 82/355 strains showed ETH MIC increase due to ethA variants only. Molecular dynamics simulations showed that the most frequent ethA substitutions were in pocket regions involved in communication with the binding site. Complementation of 18 ethA mutations with a wild-type copy of the gene showed MIC reduction compared to parental strains.
Combining laboratory and computational testing, we validated the role of ethA mutations to further support the implementation of genotypic drug susceptibility testing (DST). Genetic complementation supports accurate genotypic-phenotypic association studies to improve the interpretation of mutations, thus enabling molecular DST towards the concept of precision medicine in infectious diseases.