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Updated: Jul 28, 2025

A Tandem Liquid Chromatography–Mass Spectrometry-based Approach for Metabolite Analysis of Staphylococcus aureus
Published on: March 28, 2017
Dielectrophoresis microbial characterization and isolation of Staphylococcus aureus based on optimum crossover
Arash Zulkarnain Ahmad Rozaini1,2, Abdullah Abdulhameed3, Revathy Deivasigamani1
1Institute of Microengineering and Nanoelectronics (IMEN), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Abstract:
Characterization of antibiotic-resistant bacteria is a significant concern that persists for the rapid classification and analysis of the bacteria. A technology that utilizes the manipulation of antibiotic-resistant bacteria is key to solving the significant threat of these pathogenic bacteria by rapid characterization profile. Dielectrophoresis (DEP) can differentiate between antibiotic-resistant and susceptible bacteria based on their physical structure and polarization properties. In this work, the DEP response of two Gram-positive bacteria, namely, Methicillin-resistant Staphylococcus aureus (MRSA) and Methicillin-susceptible S. aureus (MSSA), was investigated and simulated. The DEP characterization was experimentally observed on the bacteria influenced by oxacillin and vancomycin antibiotics. MSSA control without antibiotics has crossover frequencies ( ) from 6 to 8 MHz, whereas MRSA control is from 2 to 3 MHz. The changed when bacteria were exposed to the antibiotic. As for MSSA, the decreased to 3.35 MHz compared to MSSA control without antibiotics, MRSA, increased to 7 MHz when compared to MRSA control. The changes in the DEP response of MSSA and MRSA with and without antibiotics were theoretically proven using MyDEP and COMSOL simulation and experimentally based on the modification to the bacteria cell walls. Thus, the DEP response can be employed as a label-free detectable method to sense and differentiate between resistant and susceptible strains with different antibiotic profiles. The developed method can be implemented on a single platform to analyze and identify bacteria for rapid, scalable, and accurate characterization.
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