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Applied and Environmental Microbiology, August 2003, p. 4566-4574, Vol. 69, No. 8
0099-2240/03/$08.00+0     DOI: 10.1128/AEM.69.8.4566-4574.2003
Copyright © 2003, American Society for Microbiology. All Rights Reserved.

Rapid Identification of Candida Species by Using Nuclear Magnetic Resonance Spectroscopy and a Statistical Classification Strategy

Uwe Himmelreich,1,2* Ray L. Somorjai,3 Brion Dolenko,3 Ok Cha Lee,1 Heide-Marie Daniel,1 Ronan Murray,1 Carolyn E. Mountford,2 and Tania C. Sorrell1,2

Centre for Infectious Diseases and Microbiology, Institute for Clinical Pathology and Medical Research, University of Sydney at Westmead Hospital, Westmead, New South Wales 2145,1 Institute for Magnetic Resonance Research and Department of Magnetic Resonance in Medicine, University of Sydney, Sydney, New South Wales 2006, Australia,2 Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, Manitoba R3B 1Y6, Canada3

Received 6 March 2003/ Accepted 3 June 2003

Nuclear magnetic resonance (NMR) spectra were acquired from suspensions of clinically important yeast species of the genus Candida to characterize the relationship between metabolite profiles and species identification. Major metabolites were identified by using two-dimensional correlation NMR spectroscopy. One-dimensional proton NMR spectra were analyzed by using a staged statistical classification strategy. Analysis of NMR spectra from 442 isolates of Candida albicans, C. glabrata, C. krusei, C. parapsilosis, and C. tropicalis resulted in rapid, accurate identification when compared with conventional and DNA-based identification. Spectral regions used for the classification of the five yeast species revealed species-specific differences in relative amounts of lipids, trehalose, polyols, and other metabolites. Isolates of C. parapsilosis and C. glabrata with unusual PCR fingerprinting patterns also generated atypical NMR spectra, suggesting the possibility of intraspecies discontinuity. We conclude that NMR spectroscopy combined with a statistical classification strategy is a rapid, nondestructive, and potentially valuable method for identification and chemotaxonomic characterization that may be broadly applicable to fungi and other microorganisms.

* Corresponding author. Mailing address: Centre for Infectious Diseases and Microbiology, University of Sydney at Westmead Hospital, Rm. 3114, Level 3, ICPMR, Darcy Rd., Westmead, New South Wales 2145, Australia. Phone: 61-2-9351 6168. Fax: 61-2-9351 4105. E-mail: uwe{at}med.usyd.edu.au.

Applied and Environmental Microbiology, August 2003, p. 4566-4574, Vol. 69, No. 8
0099-2240/03/$08.00+0     DOI: 10.1128/AEM.69.8.4566-4574.2003
Copyright © 2003, American Society for Microbiology. All Rights Reserved.



This article has been cited by other articles:

  • Coen, M., Bodkin, J., Power, D., Bubb, W. A., Himmelreich, U., Kuchel, P. W., Sorrell, T. C. (2006). Antifungal Effects on Metabolite Profiles of Medically Important Yeast Species Measured by Nuclear Magnetic Resonance Spectroscopy. Antimicrob. Agents Chemother. 50: 4018-4026 [Abstract] [Full Text]  
  • Shulaev, V. (2006). Metabolomics technology and bioinformatics. Brief Bioinform 7: 128-139 [Abstract] [Full Text]  
  • Himmelreich, U., Accurso, R., Malik, R., Dolenko, B., Somorjai, R. L., Gupta, R. K., Gomes, L., Mountford, C. E., Sorrell, T. C. (2005). Identification of Staphylococcus aureus Brain Abscesses: Rat and Human Studies with 1H MR Spectroscopy. Radiology 236: 261-270 [Abstract] [Full Text]  


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