Rapid Identification and Typing of Carbapenem-Resistant Klebsiella pneumoniae Using MALDI-TOF MS and Machine Learning
- PMID: 40522100
- PMCID: PMC12168492
- DOI: 10.1111/1751-7915.70184
Rapid Identification and Typing of Carbapenem-Resistant Klebsiella pneumoniae Using MALDI-TOF MS and Machine Learning
Abstract
Use matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to screen the specific mass peaks of carbapenem-resistant Klebsiella pneumoniae (CRKP), compare the differences in spectrum peaks between intestinal and bloodstream screening of CRKP, and assess the utility of MALDI-TOF MS in quickly identifying various CRKP sources. From 2014 to 2023, a total of 267 Klebsiella pneumoniae strains were collected at Quzhou People's Hospital, including 60 intestinal screening isolates from ICU patients and 207 bloodstream infection isolates. MALDI-TOF MS was used to profile peptides in CRKP and carbapenem-sensitive Klebsiella pneumoniae (CSKP), followed by analysis with flexAnalysis and ClinProTools 3.0. Statistically significant protein peaks were selected to build classification models, which were verified using non-duplicate strains. MALDI-TOF MS achieved > 99.9% accuracy in identifying Klebsiella pneumoniae. Characteristic peaks (2523.43, 3041.62, 4520.11, 10,079.18 Da) were used to develop resistance analysis models, with the optimal model (SNN) showing 90.08% sensitivity, 95.80% specificity and identification accuracies of 90% for CSKP and 89.66% for CRKP. Another model using peaks (8876, 8993, 9139 Da) differentiated CRKP origins, with the ideal model (QC) achieving 86.85% sensitivity, 88.46% specificity, and accuracies of 81.82% for bloodstream and 95.00% for intestinal CRKP.
Keywords: Klebsiella pneumonia; GA; MALDI‐TOF MS; QC; SNN; bloodstream infection; carbapenemase; characteristic peak.
© 2025 The Author(s). Microbial Biotechnology published by John Wiley & Sons Ltd.
Conflict of interest statement
The authors declare no conflicts of interest.
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