Evaluation of Oxford Nanopore Sequencing for Antimicrobial Resistance Surveillance in Salmonella: Comparison with Phenotypic Antimicrobial Susceptibility in a Large-Scale Study
Yu-Ping HongiD, Ying-Shu Liao, You-Wun WangiD, Shao-Chun Kuo, Ru-Hsiou Teng, Shiu-Yun Liang, Jui-Hsien Chang, Hsiao-Lun Wei, Chien‐Shun ChiouiD
Abstract
Salmonella is a major zoonotic foodborne pathogen, and antimicrobial resistance (AMR) in Salmonella presents a significant public health challenge. Whole-genome sequencing (WGS) offers a more rapid and comprehensive method for AMR characterization compared to conventional antimicrobial susceptibility testing (AST), supporting antimicrobial therapy and surveillance efforts. In this study, Oxford Nanopore Technology (ONT)-based WGS was performed on 1,490 Salmonella isolates collected through nationwide surveillance in Taiwan in 2025. Genotypic resistance inferred from WGS data was compared with phenotypic AST results to assess the performance of ONT-WGS. Overall, WGS-inferred resistance showed high concordance with phenotypic resistance for most antimicrobials. However, major genotype- phenotype discordance was observed, attributed to four categories: (i) breakpoint-dependent classification, (ii) reduced or absent phenotypic expression of resistance genes, (iii) MIC modulation by ramAp, and (iv) absence of known AMR determinants. Notable discrepancies included tigecycline resistance without known genetic determinants, nalidixic acid resistance linked to ramAp-mediated MIC elevation, and a high prevalence of colistin resistance (35.4%) in S. Enteritidis without identifiable AMR determinants. Additionally, a significant proportion of ESBL- and AmpC-producing isolates were classified as susceptible or intermediate to cefotaxime and ceftazidime under CLSI criteria, highlighting the potential for misclassification and treatment failure. These findings demonstrate that ONT-WGS enables accurate, comprehensive AMR characterization, offering direct identification of AMR determinants and minimizing misclassification due to breakpoint-based AST interpretations. When interpreted appropriately, WGS can support better antimicrobial selection and serve as a valuable alternative to conventional susceptibility testing.
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