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Predicting Phenotypic Antimicrobial Resistance in Escherichia coli Isolates, Using Whole Genome Sequencing Data

Other Titles
 전장유전체 분석을 통한 대장균의 항균제 내성 표현형의 예측 
Authors
 Hyunsoo Kim  ;  Young Ah Kim  ;  Young Hee Seo  ;  Hyukmin Lee  ;  Kyungwon Lee 
Citation
 Annals of Clinical Microbiology, Vol.25(4) : 127-132, 2022-12 
Journal Title
Annals of Clinical Microbiology
ISSN
 2288-0585 
Issue Date
2022-12
Keywords
Antimicrobial resistance ; Phenotype ; Genotype ; Whole genome sequencing ; Escherichia coli
Abstract
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.
Files in This Item:
T9992022872.pdf Download
DOI
10.5145/ACM.2022.25.4.2
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Laboratory Medicine (진단검사의학교실) > 1. Journal Papers
Yonsei Authors
Lee, Kyungwon(이경원) ORCID logo https://orcid.org/0000-0003-3788-2134
Lee, Hyuk Min(이혁민) ORCID logo https://orcid.org/0000-0002-8523-4126
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/193912
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