Rapid identification of Candida species by using nuclear magnetic resonance spectroscopy and a statistical classification strategy

Abstract

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.

FIG. 1.

Representative ¹H NMR spectra from suspensions of Candida species in PBS-D₂O. (A) C. albicans, (B) C. krusei, (C) C. glabrata, (D) C. parapsilosis, and (E) C. tropicalis. Signal assignment was performed by using {¹H, ¹H} COSY and {¹H, ¹³C} HSQC spectra. Abbreviations: CHOH, carbohydrate and polyol residues; eth, ethanol; lip, lipids; and N(CH₃)₃, betaine- and choline-containing metabolites (mainly glycerophosphocholine). Signal assignment was made from COSY spectra except for polyols and carbohydrate residues, when {¹H, ¹³C} correlation NMR spectra (HMBC and HSQC) were used. ¹H NMR spectra were obtained after processing in xwinnmr (multiplication with an exponential function resulting in a line broadening of 1 Hz, Fourier transformation, first- and second-order phase correction, and polynomial baseline correction).

FIG. 2.

Accuracy of the classification of Candida species with increasing numbers of isolates. Classifiers were developed as isolates became available. A first set of pairwise classifiers was developed on 162 cultures. The accuracy of the classifiers on the training set is indicated by crosses. These classifiers were then tested against an independent validation set of cultures (circles). Only the number of cultures used for the development of classifiers (training set) is indicated. For number of cultures in the validation set, see Table 2. Accuracy was determined based on correct identification (compared to PCR fingerprinting). Isolates belonging to species not included in this study but part of the validation data sets were not considered.