Surface Enhanced Raman Spectroscopy for urinary tract infection diagnosis and antibiogram

摘要

Urinary tract infection diagnosis and antibiogram require a minimum of 48 hours using standard laboratory practice. This long waiting period contributes to an increase in recurrent infections, rising health care costs, and a growing number of bacterial strains developing resistance to antibiotics. In this work, Surface Enhanced Raman Spectroscopy (SERS) was used as a novel method for classifying bacteria and determining their antibiogram. Five species of bacteria were classified with > 90% accuracy using their SERS spectra and a classification algorithm involving novel feature extraction and discriminant analysis. Antibiotic resistance or sensitivity was determined after just a two-hour exposure of bacteria to ciprofloxacin (sensitive) and amoxicillin (resistant) and analysis of their SERS spectra. These results can become the basis for the development of a novel method that would provide same day diagnosis and selection of the most appropriate antibiotic for most effective treatment of a urinary tract infection.