Paper
2 February 2012 Complete urinary tract infection (UTI) diagnosis and antibiogram using surface enhanced Raman spectroscopy (SERS)
Katerina Hadjigeorgiou, Evdokia Kastanos, Alexandros Kyriakides, Costas Pitris
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Abstract
There are three stages to a complete UTI diagnosis: (1) identification of a urine sample as positive/negative for an infection, (2) identification of the responsible bacterium, (3) antibiogram to determine the antibiotic to which the bacteria are most sensitive to. Using conventional methods, all three stages require bacterial cultures in order to provide results. This long delay in diagnosis causes a rise in ineffective treatments, chronic infections, health care costs and antibiotic resistance. In this work, SERS is used to identify a sample as positive/negative for a UTI as well as to obtain an antibiogram against different antibiotics. SERS spectra of serial dilutions of E. coli bacteria mixed with silver nanoparticles, showed a linear correlation between spectral intensity and concentration. For antibiotic sensitivity testing, SERS spectra of three species of gram negative bacteria were collected four hours after exposure to the antibiotics ciprofloxacin and amoxicillin. Spectral analysis revealed clear separation between bacterial samples exposed to antibiotics to which they were sensitive and samples exposed to antibiotics to which they were resistant. With the enhancement provided by SERS, the technique can be applied directly to urine samples leading to the development of a new, rapid method for UTI diagnosis and antibiogram.
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Katerina Hadjigeorgiou, Evdokia Kastanos, Alexandros Kyriakides, and Costas Pitris "Complete urinary tract infection (UTI) diagnosis and antibiogram using surface enhanced Raman spectroscopy (SERS)", Proc. SPIE 8229, Optical Diagnostics and Sensing XII: Toward Point-of-Care Diagnostics; and Design and Performance Validation of Phantoms Used in Conjunction with Optical Measurement of Tissue IV, 82290D (2 February 2012); https://doi.org/10.1117/12.907997
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Cited by 5 scholarly publications.
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KEYWORDS
Bacteria

Surface enhanced Raman spectroscopy

Raman spectroscopy

Nanoparticles

Statistical analysis

Resistance

Silver

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