Abstract
The emergence of resistance to azithromycin complicates treatment of Neisseria gonorrhoeae, the etiologic agent of gonorrhea. Substantial azithromycin resistance remains unexplained after accounting for known resistance mutations. Bacterial genome-wide association studies (GWAS) can identify novel resistance genes but must control for genetic confounders while maintaining power. Here, we show that compared to single-locus GWAS, conducting GWAS conditioned on known resistance mutations reduces the number of false positives and identifies a G70D mutation in the RplD 50S ribosomal protein L4 as significantly associated with increased azithromycin resistance (p-value = 1.08 × 10−11). We experimentally confirm our GWAS results and demonstrate that RplD G70D and other macrolide binding site mutations are prevalent (present in 5.42% of 4850 isolates) and widespread (identified in 21/65 countries across two decades). Overall, our findings demonstrate the utility of conditional associations for improving the performance of microbial GWAS and advance our understanding of the genetic basis of macrolide resistance.
Highlights
The emergence of resistance to azithromycin complicates treatment of Neisseria gonorrhoeae, the etiologic agent of gonorrhea
We find that conventional single-locus bacterial genome-wide association studies (GWAS) approaches lead to confounded results and reduced power, but conducting GWAS conditional on known resistance mutations in 23S rRNA reduces linkage-mediated confounding and increases power to recover mutations associated with lower-level resistance
After conducting GWAS on the 4505 isolates with associated azithromycin minimum inhibitory concentrations (MICs), we identified highly significant unitigs mapping to the 23S rRNA, associated with increased resistance, and to the efflux pump gene mtrC, associated with increased susceptibility and cervical infections[7]
Summary
The emergence of resistance to azithromycin complicates treatment of Neisseria gonorrhoeae, the etiologic agent of gonorrhea. We show that compared to single-locus GWAS, conducting GWAS conditioned on known resistance mutations reduces the number of false positives and identifies a G70D mutation in the RplD 50S ribosomal protein L4 as significantly associated with increased azithromycin resistance (p-value = 1.08 × 10−11). We find that conventional single-locus bacterial GWAS approaches lead to confounded results and reduced power, but conducting GWAS conditional on known resistance mutations in 23S rRNA reduces linkage-mediated confounding and increases power to recover mutations associated with lower-level resistance. We experimentally validate one such mutation in the 50S ribosomal protein RplD and identify other rare RplD variants associated with resistance, highlighting the ability of conditional bacterial GWAS to discover causal genes for polygenic microbial phenotypes
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