Paper
25 February 2013 Urinary tract infection (UTI) multi-bacteria multi-antibiotic testing using surface enhanced Raman spectroscopy (SERS)
Katerina Hadjigeorgiou , Evdokia Kastanos, Costas Pitris
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Abstract
Antibiotic resistance is a major health care problem mostly caused by the inappropriate use of antibiotics. At the root of the problem lies the current method for determination of bacterial susceptibility to antibiotics which requires overnight cultures. Physicians suspecting an infection usually prescribe an antibiotic without waiting for the results. This practice aggravates the problem of bacterial resistance. In this work, a rapid method of diagnosis and antibiogram for a bacterial infection was developed using Surface Enhanced Raman Spectroscopy (SERS) with silver nanoparticles. SERS spectra of three species of gram negative bacteria, Escherichia coli, Proteus spp., and Klebsiella spp. were obtained after 0 and 4 hour exposure to the seven different antibiotics. Even though the concentration of bacteria was low (2x105 cfu/ml), species classification was achieved with 94% accuracy using spectra obtained at 0 hours. Sensitivity or resistance to antibiotics was predicted with 81%-100% accuracy from spectra obtained after 4 hours of exposure to the different antibiotics. With the enhancement provided by SERS, the technique can be applied directly to urine or blood samples, bypassing the need for overnight cultures. This technology can lead to the development of rapid methods of diagnosis and antibiogram for a variety of bacterial infections.
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Katerina Hadjigeorgiou , Evdokia Kastanos, and Costas Pitris "Urinary tract infection (UTI) multi-bacteria multi-antibiotic testing using surface enhanced Raman spectroscopy (SERS)", Proc. SPIE 8591, Optical Diagnostics and Sensing XIII: Toward Point-of-Care Diagnostics, 85910B (25 February 2013); https://doi.org/10.1117/12.2003523
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Cited by 4 scholarly publications.
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KEYWORDS
Surface enhanced Raman spectroscopy

Bacteria

Nanoparticles

Resistance

Raman spectroscopy

Silver

Intelligence systems

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