# The Synergistic Armory: A Global Genome-Wide Association Study Reveals the Integrated Mechanisms of Azithromycin Resistance in Neisseria gonorrhoeae

## TL;DR

This study identifies genetic factors contributing to azithromycin resistance in Neisseria gonorrhoeae, revealing multiple genes and interactions that help the bacteria survive the antibiotic.

## Contribution

The study reveals new genetic variants and synergistic interactions that contribute to azithromycin resistance in Neisseria gonorrhoeae.

## Key findings

- 113 genetic variants were found to be significantly associated with azithromycin resistance in Neisseria gonorrhoeae.
- Multiple amino acid substitutions in ribosomal proteins and porin alterations were identified as resistance determinants.
- Phylogenetic analysis revealed distinct resistance strategies in globally circulating lineages of Neisseria gonorrhoeae.

## Abstract

Azithromycin remains an important agent in gonorrhea treatment, yet resistance is a growing global threat. To comprehensively define its genetic basis, we performed a large-scale genome-wide association study of 14,727 Neisseria gonorrhoeae genomes with linked azithromycin MICs from 66 countries. We identified 113 genetic variants significantly associated with elevated MICs. Beyond well-known mutations in 23S rRNA (A2059G, C2611T) and mtrCDE operon, we uncovered a broad repertoire of potential resistance determinants, including multiple amino acid substitutions in 16 ribosomal proteins (e.g., L2, L4, L13, L23) forming the nascent peptide exit tunnel (NPET), and porin PorB alterations (G120K, A121D/N). Systematic pairwise analysis revealed extensive synergistic interactions, particularly between variants affecting drug influx/efflux (PorB, MtrCDE) and ribosomal target affinity. Phylogenetic analysis identified successful, globally circulating lineages employing distinct resistance strategies: NPET-dominated, 23S rRNA-associated, and porin/efflux-mediated. Our findings demonstrate that azithromycin resistance is a polygenic trait shaped by functional complementarity and epistasis between target modification, membrane permeability, and efflux. This integrated model is essential for accurate resistance prediction from genomic data and highlights key lineages for focused surveillance.