Evaluation of the Quantum II yeast identification system

Yeast identification--past, present, and future methods

The focus of this review is the evolution of biochemical phenotypic yeast identification methods with emphasis on conventional approaches, rapid screening tests, chromogenic agars, comprehensive commercial methods, and the eventual migration to genotypic methods. As systemic yeast infections can be devastating and resistance is common in certain species, accurate identification to the species level is paramount for successful therapy and appropriate patient care.

Automated systems for identification of microorganisms

Automated instruments for the identification of microorganisms were introduced into clinical microbiology laboratories in the 1970s. During the past two decades, the capabilities and performance characteristics of automated identification systems have steadily progressed and improved. This article explores the development of the various automated identification systems available in the United States and reviews their performance for identification of microorganisms. Observations regarding deficiencies and suggested improvements for these systems are provided.

Evaluation of the API ATB 32C system for the rapid identification of foodborne yeasts

The commercial API ATB 32C identification kit was compared with a standard method for identifying 11 reference strains and 53 yeast strains isolated from fermented milk products. Approx. 50% of the species considered in the API ATB 32C database were identified on a level of good, very good, and excellent identification. The numerical profile of 25 strains was not found in the API ATB 32C index. Low discrimination or misidentification was observed in seven strains. The low reliability of the API ATB 32C system may be ascribed to the incomplete nature of the profile index. A majority (91%) of the strains, however, were identified correctly by the API ATB 32C strip test results in combination with the commercial computer program of Barnett et al. (1985). This combined procedure offers the possibility to identify any out of 497 species considered by Barnett et al. (1985).

Comparison of the Quantum II, API Yeast Ident, and AutoMicrobic systems for identification of clinical yeast isolates

The Quantum II Yeast Identification System (Abbott Laboratories) is a microprocessor-based spectrophotometric system for identification of clinical yeast isolates within 24 h. We compared the Quantum II system with the API Yeast Ident (Analytab Products) and the AutoMicrobic System Yeast Biochemical Card (AMS-YBC; Vitek Systems, Inc.) for the identification of 221 clinical yeast isolates, including 120 common clinical isolates (Candida albicans, C. tropicalis, C. parapsilosis, Torulopsis glabrata, and Cryptococcus neoformans) and 101 relatively uncommon clinical isolates. The API 20C (Analytab) was used as the reference system. The Quantum II and AMS-YBC systems correctly identified 181 (82%) and 184 (83%) isolates, respectively, whereas the Yeast Ident system correctly identified 132 (60%) isolates. Of the 120 common clinical isolates, 113 (94%) were correctly identified by Quantum II, 103 (86%) were correctly identified by AMS-YBC, and 83 (69%) were correctly identified by Yeast Ident. Of the 101 uncommon clinical isolates tested, 68 (67%) were correctly identified by Quantum II, 81 (80%) were correctly identified by AMS-YBC, and 49 (49%) were correctly identified by Yeast Ident. The overall accuracy of the Quantum II, AMS-YBC, and API Yeast Ident was not sufficient to recommend any of these systems for routine use in the clinical microbiology laboratory without substantial expansion of the respective data bases.

Evaluation of simplified and commercial systems for identification of foodborne yeasts

Commercial identification kits (API 20C, API Yeast-Ident and API-Zym) were compared with a conventional but simplified identification method (SIM) for identifying seventy-two yeast isolates from fresh sweet corn. SIM failed to provide identification of two isolates. Of the twenty species identified, only eleven were included in the API 20C profile index. Three isolates were identified at the species level and three were identified at the genus level with 100% accuracy. The enzyme kit (Yeast-Ident) gave rather unreliable results, in that identification of only four isolates with 75 to 85% of appropriate reactions was made. The API 20C kit could be used to identify non-clinical yeasts, provided they were included in its database and a few additional tests (urease reaction, nitrate assimilation and glucose fermentation) were also performed.

Uncommon yeastlike zoopathogens and commercial systems for their identification

Opportunistic infections caused by yeasts or yeastlike fungi have increased in incidence in recent years as a result of clinical and therapeutic factors. Several formerly uncommon yeastlike zoopathogens--Candida lusitaniae, Candida paratropicalis (sucrose-negative variant of Candida tropicalis), Trichosporon beigelii, Blastoschizomyces capitatus, and Rhodotorula species--have been isolated from patients with invasive infections. The increased isolation of such opportunistic pathogens from a variety of clinical specimens has created a demand for simple, rapid, reliable, and accurate commercial systems to assist laboratorians in identification. Here we summarize the manual and automated systems currently available and present detailed descriptions of three representative commercial products, i.e., API 20C, Abbott Quantum II, and API Yeast-Ident.

Conventional and rapid methods for yeast identification

Identification of yeasts depends on data obtained from morphological features and physiological characteristics. This article reviews the commonly used conventional methods for the identification of yeast to set the stage for a critical review of rapid systems for yeast identification. Comparative analyses of percentage agreement of API 20C, Uni-Yeast Tek, Minitek, Mycotube, Micro-Drop, Auxodisk, Iatron, Autobac 1, AMS, Abbott MS-2, and Abbott Quantum 11 against the conventional method and, in some cases, against each other are tabulated. Gas liquid chromatography method, enzyme method, MUG, and the Fung's mini-system are also mentioned as possible rapid methods for yeast identification. The purpose of this review is to update the rapidly expanding information concerning diagnostic kits and systems for yeast identification and analyze some of the advantages, disadvantages and potential uses of rapid systems of yeast identification.

Rapid identification of yeasts by semi-automated and conventional methods

Five different methods for the identification of significant yeast from clinical specimens were compared for their reliability, rapidity and cost-effectiveness. Three commercial methods consisted of semi-automated Abbott's yeasts identification system using MS-2 (Abbott Laboratories, Diagnostic Division, Irving, Texas), API 20C (Analytab Products, Inc., Plainview, NY) and Uni-Yeast-Tek (Flow Labs, Inc., MacLean, VA). Two conventional methods included the modified dye-plur plate auxanographic and rapid tube assimilation method. The 242 coded clinical isolates used in this study included 20 species of Candida, Cryptococcus, Saccharomyces Geotrichum, Rhodotorula, Torulopsis and Trichosporon. The identification accuracies with all the systems ranges between 92.3% to 97.5%. Results were available with Abbott's MS-2 within 24 h, with rapid tube assimilation method in 6-48 h and in 72 h with other systems. Rapid tube assimilation and dye-pour-plate auxanographic methods were least expensive, with labour and material costing around $1.00 per identification, whereas the commercial system cost a little over $5.00.