DISCRIMINATION BETWEEN METHICILLIN-RESISTANT AND METHICILLIN-SUSCEPTIBLE STAPHYLOCOCCUS-AUREUS USING PYROLYSIS MASS-SPECTROMETRY AND ARTIFICIAL NEURAL NETWORKS
R. Goodacre et al., DISCRIMINATION BETWEEN METHICILLIN-RESISTANT AND METHICILLIN-SUSCEPTIBLE STAPHYLOCOCCUS-AUREUS USING PYROLYSIS MASS-SPECTROMETRY AND ARTIFICIAL NEURAL NETWORKS, Journal of antimicrobial chemotherapy, 41(1), 1998, pp. 27-34
Curie-point pyrolysis mass spectra were obtained from 15 methicillin-r
esistant and 22 methicillin-susceptible Staphylococcus aureus strains,
Cluster analysis showed that the major source of variation between th
e pyrolysis mass spectra resulted from the phage group of the bacteria
, not their resistance or susceptibility to methicillin. By contrast,
artificial neural networks could be trained to recognize those aspects
of the pyrolysis mass spectra that differentiated methicillin-resista
nt from methicillin-sensitive strains. The trained neural network coul
d then use pyrolysis mass spectral data to assess whether an unknown s
train was resistant to methicillin. These results give the first demon
stration that the combination of pyrolysis mass spectrometry with neur
al networks can provide a very rapid and accurate antibiotic susceptib
ility testing technique.