Impact of population structure in the design of RNA-based diagnostics for antibiotic resistance in Neisseria gonorrhoeae

Abstract

Quantitative assessment of antibiotic-responsive RNA transcripts holds promise for a rapid point of care (POC) diagnostic tool for antimicrobial susceptibility testing. These assays aim to distinguish susceptible and resistant isolates by transcriptional differences upon drug exposure. However, an often-overlooked dimension of designing these tests is that the genetic diversity within a species may yield differential transcriptional regulation independent of resistance phenotype. Here, we use a phylogenetically diverse panel of Neisseria gonorrhoeae and transcriptome profiling coupled with RT-qPCR to test this hypothesis, to identify azithromycin responsive transcripts and evaluate their potential diagnostic value, and to evaluate previously reported diagnostic markers for ciprofloxacin resistance (porB and rpmB). Transcriptome profiling confirmed evidence of population structure in transcriptional response to azithromycin. Taking this population structure into account, we found azithromycin-responsive transcripts overrepresented in susceptible strains compared to resistant strains, and selected four candidate diagnostic transcripts (rpsO, rplN, omp3, and NGO1079) that were the most significantly differentially regulated between phenotypes across drug exposure. RNA signatures for these markers categorically predicted resistance in 19/20 cases, with the one incorrect categorical assignment for an isolate at the threshold of reduced susceptibility. Finally, we found that porB and rpmB expression were not diagnostic of ciprofloxacin resistance in a panel of isolates with unbiased phylogenetic sampling. Overall, our results suggest that RNA signatures as a diagnostic tool are promising for future POC diagnostics; however, development and testing should consider representative genetic diversity of the target pathogen.