Applied and Environmental Microbiology, February 2007, p. 1036-1040, Vol. 73, No. 3
0099-2240/07/$08.00+0 doi:10.1128/AEM.02004-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
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Abteilung Mikrobiologie, Zentralinstitut für Ernährungs- und Lebensmittelforschung, Technische Universität München, D-85350 Freising, Germany,1 Synthon GmbH, Im Neuenheimer Feld 583, D-69120 Heidelberg, Germany2
Received 23 August 2006/ Accepted 18 November 2006
A classification system based on Fourier transform infrared (FTIR) spectroscopy combined with artificial neural network analysis was designed to differentiate 12 serovars of Listeria monocytogenes using a reference database of 106 well-defined strains. External validation was performed using a test set of another 166 L. monocytogenes strains. The O antigens (serogroup) of 164 strains (98.8%) could be identified correctly, and H antigens were correctly determined in 152 (91.6%) of the test strains. Importantly, 40 out of 41 potentially epidemic serovar 4b strains were unambiguously identified. FTIR analysis is superior to PCR-based systems for serovar differentiation and has potential for the rapid, simultaneous identification of both species and serovar of an unknown Listeria isolate by simply measuring a whole-cell infrared spectrum.
Published ahead of print on 1 December 2006.
Supplemental material for this article may be found at http://aem.mcb.org/.
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