Discrimination between Carbapenem-Resistant and Carbapenem-Sensitive Klebsiella pneumoniae Strains through Computational Analysis of Surface-Enhanced Raman Spectra: a Pilot Study
Wei Liu, Jia-Wei Tang, Jingwen Lyu, Jun-Jiao Wang, Ya-Cheng Pan, Xin-Yi Shi, Qinghua Liu, Xiao Zhang, Bing Gu, Liang Wang
Abstract
With the low-cost, label-free, and nondestructive features, Raman spectroscopy is becoming an attractive technique with great potential to discriminate bacterial infections. In this pilot study, we analyzed surfaced-enhanced Raman spectroscopy (SERS) spectra via supervised machine learning algorithms, through which we confirmed the application potentials of the SERS technique in rapid and accurate discrimination of Klebsiella pneumoniae strains with different antibiotic resistance profiles.
Topics & Concepts
Klebsiella pneumoniaeSurface-enhanced Raman spectroscopyRaman spectroscopyKlebsiellaAntibioticsAntibiotic resistanceMicrobiologyCarbapenemArtificial intelligenceMachine learningBiologyRaman scatteringComputer scienceEscherichia coliPhysicsGeneOpticsGeneticsSpectroscopy Techniques in Biomedical and Chemical ResearchBacterial Identification and Susceptibility TestingBiosensors and Analytical Detection