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Abstract <p><b>Objective:</b> To characterize the antimicrobial resistance gene (ARG) profiles of the WHO 2024 <i>N. gonorrhoeae</i> reference strains and compare the CARD/RGI and NG-STAR genotyping methods. <b>Methods:</b> We performed in silico analysis of 29 reference genomes using the Resistance Gene Identifier (RGI) tool and the Comprehensive Antibiotic Resistance Database (CARD), benchmarking results against the NG-STAR scheme. <b>Results and Discussion:</b> β-Lactam and macrolide resistance genes were most prevalent. Key determinants included <i>mtrA</i>, <i>penA</i>, <i>rpsJ</i>, and <i>mtrC</i>. Strains WHO_Q and WHO_beta harbored the most ARGs (10 each). Concordance between CARD/RGI and NG-STAR was 39.4%, with CARD providing broader mechanistic coverage and NG-STAR offering superior allele-level resolution. <b>Conclusions:</b> The study provides a benchmark for genomic AMR prediction, demonstrating the complementary value of general-purpose and species-specific typing schemes for surveillance.</p>

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Genomic Analysis of Antimicrobial Resistance Determinants in the Neisseria gonorrhoeae

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • E. A. Kochubei,
  • Z. R. Zenchenko,
  • S. K. Dobrovolskii

摘要

Abstract

Objective: To characterize the antimicrobial resistance gene (ARG) profiles of the WHO 2024 N. gonorrhoeae reference strains and compare the CARD/RGI and NG-STAR genotyping methods. Methods: We performed in silico analysis of 29 reference genomes using the Resistance Gene Identifier (RGI) tool and the Comprehensive Antibiotic Resistance Database (CARD), benchmarking results against the NG-STAR scheme. Results and Discussion: β-Lactam and macrolide resistance genes were most prevalent. Key determinants included mtrA, penA, rpsJ, and mtrC. Strains WHO_Q and WHO_beta harbored the most ARGs (10 each). Concordance between CARD/RGI and NG-STAR was 39.4%, with CARD providing broader mechanistic coverage and NG-STAR offering superior allele-level resolution. Conclusions: The study provides a benchmark for genomic AMR prediction, demonstrating the complementary value of general-purpose and species-specific typing schemes for surveillance.