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KMID : 1142720220250040127
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Annals of Clinical Microbiology
2022 Volume.25 No. 4 p.127 ~ p.132
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Predicting Phenotypic Antimicrobial Resistance in Escherichia coli Isolates, Using Whole Genome Sequencing Data
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Kim Hyun-Soo
Kim Young-Ah
Seo Young-Hee
Lee Hyuk-Min
Lee Kyung-Won
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Abstract
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Background: The application of genotypic antimicrobial sensitivity tests (ASTs) is dependent on the reliability of the predictions of phenotypic resistance. In this study, routine AST results and the presence of corresponding antimicrobial resistance genes were compared.
Methods: Eighty-four extended-spectrum-β-lactamase-producing Escherichia coli isolates from poultry-related samples were included in the study. The disk diffusion method was used to test for susceptibility to antimicrobial compounds, except colistin susceptibility, which was tested using the agar dilution method. Whole-genome sequencing (WGS) was performed using a NextSeq 550 instrument (Illumina, USA). Antimicrobial resistance genes were detected using ResFinder 4.1.
Results: Concordance rates between the genotype and phenotype ranged from 35.7%(ciprofloxacin) to 96.4%(tetracycline). The presence of tet was a good predictor of phenotypic resistance.
Conclusion: The genotype was a good predictor of tetracycline phenotypic resistance, but there was a gap in the prediction of phenotypic ASTs for trimethoprim-sulfamethoxazole, chloramphenicol, gentamicin, and ciprofloxacin. We concluded that WGS-based genotypic ASTs are inadequate to replace routine phenotypic ASTs.
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KEYWORD
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Antimicrobial resistance, Phenotype, Genotype, Whole genome sequencing, Escherichia coli
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