BibTex format
@article{Cholsaktrakool:2025:10.1016/j.isci.2025.112962,
author = {Cholsaktrakool, P and Kawang, K and Sangpiromapichai, N and Thongsuk, P and Anuntakarun, S and Kunadirek, P and Chuaypen, N and Nilgate, S and Kueakulpattana, N and Rirerm, U and Chatsuwan, T and Jauneikaite, E and Davies, F and Pratanwanich, PN and Sriswasdi, S and Nilaratanakul, V},
doi = {10.1016/j.isci.2025.112962},
journal = {iScience},
title = {Inference of Antimicrobial Resistance (AMR) from a whole genome database outperforming AMR gene detection},
url = {http://dx.doi.org/10.1016/j.isci.2025.112962},
volume = {28},
year = {2025}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - This study focuses on the rapid detection of antimicrobial resistance (AMR) in Klebsiella pneumoniae. The "Align-Search-Infer" pipeline aligned query sequences from 24 urine samples against a curated genome database of 40 Klebsiella isolates, searched for the best matches, and inferred their antimicrobial susceptibility. Carbapenem resistance inference achieved 77.3% accuracy (95%CI: 59.8–94.8%) within 10 minutes using whole-genome matching, and 85.7% accuracy (95%CI: 70.7–100.0%) within 1 hour using plasmid matching—both surpassing the 54.2% accuracy (95%CI: 34.2–74.1%) of AMR gene detection at 6 hours. The proposed method requires less bacterial DNA and is suitable for low-load clinical samples. Our small local database performed comparably to large public databases. This study supports the integration of pathogen-specific genome databases into clinical workflows to enable rapid and accurate antimicrobial susceptibility prediction. Further research is needed to validate and refine the method using larger genomic-phenotypic datasets across diverse pathogens and sample types.
AU - Cholsaktrakool,P
AU - Kawang,K
AU - Sangpiromapichai,N
AU - Thongsuk,P
AU - Anuntakarun,S
AU - Kunadirek,P
AU - Chuaypen,N
AU - Nilgate,S
AU - Kueakulpattana,N
AU - Rirerm,U
AU - Chatsuwan,T
AU - Jauneikaite,E
AU - Davies,F
AU - Pratanwanich,PN
AU - Sriswasdi,S
AU - Nilaratanakul,V
DO - 10.1016/j.isci.2025.112962
PY - 2025///
SN - 2589-0042
TI - Inference of Antimicrobial Resistance (AMR) from a whole genome database outperforming AMR gene detection
T2 - iScience
UR - http://dx.doi.org/10.1016/j.isci.2025.112962
UR - https://doi.org/10.1016/j.isci.2025.112962
VL - 28
ER -