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Journal of Clinical Microbiology, September 2006, p. 3167-3171, Vol. 44, No. 9
0095-1137/06/$08.00+0 doi:10.1128/JCM.00390-06
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Microbial Genomics and Bioprocessing Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture, Peoria, Illinois,1 Microbiology Division, Department of Pathology, The Johns Hopkins Medical Institutions, Baltimore, Maryland2
Received 21 February 2006/ Returned for modification 8 June 2006/ Accepted 14 July 2006
This study was designed to compare the identification of ascomycetous yeasts recovered from clinical specimens by using phenotypic assays (PA) and a molecular flow cytometric (FC) method. Large-subunit rRNA domains 1 and 2 (D1/D2) gene sequence analysis was also performed and served as the reference for correct strain identification. A panel of 88 clinical isolates was tested that included representatives of nine commonly encountered species and six infrequently encountered species. The PA included germ tube production, fermentation of seven carbohydrates, morphology on corn meal agar, urease and phenoloxidase activities, and carbohydrate assimilation tests when needed. The FC method (Luminex) employed species-specific oligonucleotides attached to polystyrene beads, which were hybridized with D1/D2 amplicons from the unidentified isolates. The PA identified 81 of 88 strains correctly but misidentified 4 of Candida dubliniensis, 1 of C. bovina, 1 of C. palmioleophila, and 1 of C. bracarensis. The FC method correctly identified 79 of 88 strains and did not misidentify any isolate but did not identify nine isolates because oligonucleotide probes were not available in the current library. The FC assay takes approximately 5 h, whereas the PA takes from 2 h to 5 days for identification. In conclusion, PA did well with the commonly encountered species, was not accurate for uncommon species, and takes significantly longer than the FC method. These data strongly support the potential of FC technology for rapid and accurate identification of medically important yeasts. With the introduction of new antifungals, rapid, accurate identification of pathogenic yeasts is more important than ever for guiding antifungal chemotherapy.
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