Rapid analysis of microbial systems using vibrational spectroscopy and supervised learning methods: application to the discrimination between methicillin-resistant and methicillin-susceptible Staphy

Royston Goodacre; Paul J. Rooney; Douglas B. Kell

doi:10.1117/12.306087

24 April 1998 Rapid analysis of microbial systems using vibrational spectroscopy and supervised learning methods: application to the discrimination between methicillin-resistant and methicillin-susceptible Staphy

Royston Goodacre, Paul J. Rooney, Douglas B. Kell

Author Affiliations +

Proceedings Volume 3257, Infrared Spectroscopy: New Tool in Medicine; (1998) https://doi.org/10.1117/12.306087
Event: BiOS '98 International Biomedical Optics Symposium, 1998, San Jose, CA, United States

Abstract

FTIR spectra were obtained from 15 methicillin-resistant and 22 methicillin-susceptible Staphylococcus aureus strains using our DRASTIC approach. Cluster analysis showed that the major source of variation between the IR spectra was not due to their resistance or susceptibility to methicillin; indeed early studies suing pyrolysis mass spectrometry had shown that this unsupervised analysis gave information on the phage group of the bacteria. By contrast, artificial neural networks, based on a supervised learning, could be trained to recognize those aspects of the IR spectra which differentiated methicillin-resistant from methicillin- susceptible strains. These results give the first demonstration that the combination of FTIR with neural networks can provide a very rapid and accurate antibiotic susceptibility testing technique.

Citation Download Citation

Royston Goodacre, Paul J. Rooney, and Douglas B. Kell "Rapid analysis of microbial systems using vibrational spectroscopy and supervised learning methods: application to the discrimination between methicillin-resistant and methicillin-susceptible Staphy", Proc. SPIE 3257, Infrared Spectroscopy: New Tool in Medicine, (24 April 1998); https://doi.org/10.1117/12.306087

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