Table of Contents Author Guidelines Submit a Manuscript
Journal of Spectroscopy
Volume 2013, Article ID 538686, 3 pages
http://dx.doi.org/10.1155/2013/538686
Research Article

Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy and Artificial Neural Networks Applied to Differentiate Escherichia coli Strains

1Department of Microbiology, Jan Kochanowski University in Kielce, Swietokrzyska Street, 25-406 Kielce, Poland
2Chair of Environmental Protection and Modeling, Jan Kochanowski University in Kielce, Swietokrzyska Street, 25-406 Kielce, Poland

Received 1 August 2012; Accepted 29 October 2012

Academic Editor: Feride Severcan

Copyright © 2013 Łukasz Lechowicz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Fimbriae are an important pathogenic factor of Escherichia coli during development of urinary tract infections. Here, we describe a new method for identification of Escherichia coli from strains using the attenuated total reflectance Fourier transform infrared Spectroscopy (ATR FT-IR). We applied artificial neural networks to the analysis of the ATR FT-IR results. These methods allowed to discriminate E. coli from strains with accuracy of 99%.