Comparison of the Rapid Yeast Plus Panel with the API20C Yeast System for Identification of Clinically Significant Isolates of Candida Species

Abstract

The RapID Yeast Plus system (Innovative Diagnostic Systems, Norcross, Ga.) is a qualitative micromethod employing conventional tests and single-substrate chromogenic tests and having a 4-h incubation period. This system was compared with the API20C (bioMerieux Vitek, Hazelwood, Mo.) system, a 24- to 72-h carbohydrate assimilation method. One hundred thirty-three clinical yeast isolates, including 57 of Candida albicans, 26 of Candida tropicalis, 23 of Candida glabrata, and 27 of other yeasts, were tested by both methods. When discrepancies occurred, isolates were further tested by the Automated Yeast Biochemical Card (bioMerieux Vitek). Germ tube production and microscopic morphology were used as needed to definitively identify yeast isolates. The RapID Yeast Plus system correctly identified 125 yeast isolates, with an overall accuracy of 94% (125 of 133). Excellent correlation was found in the recognition of the three yeasts most commonly isolated from human sources. The test was 99% (105 of 106 isolates) accurate with C. albicans,C. tropicalis, and C. glabrata. The RapID Yeast Plus system compares favorably with the API20C system and provides a simple, accurate alternative to conventional assimilation methods for the rapid identification of the most commonly encountered isolates ofCandida species.

Identification of clinically relevant yeast species by DNA sequence analysis of the D2 variable region of the 25–28S rRNA gene

“…When conflicting results between RapID and D2-based identification were observed, the API 20C AUX slightly increased the concordance level, lowering from 11 ⁄ 53 to nine of 53 discordant identifications. These observations confirm the validity of the API 20C AUX for phenotypic identification, 8,11 and pose the problem of whether the limited repertoire of carbon sources and ⁄ or the short time available for substrate reaction and ⁄ or subjective reading can occasionally result in misidentification of some Candida species by the RapID system, as previously documented for C. parapsilosis 8,50 and other yeast species. 9,26 The estimated cost of in-house D2 sequence-based identification, from yeast thermolysis to data reporting, calculated on five samples per day using the official price lists for ingredients and supplies, was approximately twice the RapID system, but less than half of the MicroSeq D2 LSU rDNA fungal identification system (Applied Biosystems), and could further be lowered if more samples are processed.…”

“…S1), and fully consistent with previously published 25-28S rRNA tree architectures of yeast. 23,50 This implies that the D2 locus retains sufficient discriminatory power for species-level differentiation, in spite of the low number of significant characters (c. 260 bp). Moreover, the D2 region of 25-28S rRNA gene offers a broad range of taxonomic resolution of yeast, as the availability of fungal D2 sequences in public databases far exceeds that of any other molecular marker (e.g.…”

Comparison of Three Commercial Systems for Identification of Yeasts Commonly Isolated in the Clinical Microbiology Laboratory

“…and other yeasts include analysis of microscopic morphologic characteristics and substrate assimilation assays (12). Since traditional methods are tedious and time-consuming to perform in the routine laboratory, numerous commercial systems that can identify these pathogens within 4 to 72 h, depending on the system, have been developed (4,6,7,9,10). The RapID Yeast Plus System is a micromethod that identifies yeasts in 4 h and has been studied by a number of investigators (3,9).…”

Pyrosequencing of a hypervariable region in the internal transcribed spacer 2 to identify clinical yeast isolates

“…However, misidentifications and database limitations have been reported in some circumstances. 13,14 In recent years, molecular approaches have been developed to improve the identification. [15][16][17] Of these, DNA sequencing of target regions is presently considered as the most precise approach to identify the microorganisms.…”