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

Comparison of use of phenotypic and genotypic characteristics for identification of species of the anamorph genus Candida and related teleomorph yeast species

A total of 49 type and neotype isolates and 32 clinical isolates of the anamorph genus Candida and related teleomorph genera were obtained from different culture collections and clinical laboratories. Isolates were subjected to two phenotypic methods of identification, Vitek yeast biochemical card (YBC) and API ID 32C, both based on carbohydrate assimilation, and one genotypic method, PCR fingerprinting, based on the detection of DNA polymorphisms between minisatellite-specific sequences with the primer M13 (5' GAGGGTGGCGGTTCT 3'). The correct identification of a strain at the Centraalbureau voor Schimmelcultures was used as the gold standard for the identification of an isolate. When the study was restricted to species included in the respective biochemical databases, the Vitek YBC and API ID 32C systems performed adequately with positive identification rates of 87.3 and 76.8%, respectively. When uncommon species were added to the study, several of which are not included in the databases, the identification efficiencies were 76.5 and 77.5%, respectively. By comparison, all isolates were correctly identified by PCR fingerprinting, with 63 reference species profiles in the databank. Sufficient polymorphisms among the total set of banding patterns were observed, with adequate similarity in the major patterns obtained from a given species, to allow each isolate to be assigned unambiguously to a particular species. In addition, variations in minor bands allowed for differentiation to the strain level. PCR fingerprinting was found to be rapid, reproducible, and more cost-effective than either biochemical approach. Our results provide reference laboratories with an improved identification method for yeasts based on genotypic rather than phenotypic markers.

Evaluation of the MicroScan enzyme-based system for the identification of foodborne yeasts

Eighty-nine strains representing 36 species of foodborne yeasts isolated from fruit juice concentrates were identified using the Baxter MicroScan enzyme-based kit, conventional tests according to a simplified identification method (SIM), and the API 20C kit. Of the 15 test species included in the MicroScan database, only 40% were correctly identified; 13% gave scores of unacceptably low probabilities, 20% were misidentified, and 27% could not be identified. Of the 21 test species not in the MicroScan database, 38% were misidentified and 62% produced biocodes with between-species differences not larger than differences between strains within species. The reliability of the MicroScan enzyme-based system is questioned, in that different results were sometimes obtained upon retesting the same strains. The MicroScan enzyme-based system is rapid, providing results within 4 h. However, because of its restricted and specific database and unreliability, the system appears to be unsuited for the identification of foodborne yeasts.

Osteomyelitis and intervertebral discitis caused by Blastoschizomyces capitatus in a patient with acute leukemia

We describe the first known case of vertebral osteomyelitis and discitis caused by Blastoschizomyces capitatus in a leukemic patient and the results of therapy. We also reconfirm the microbiological characteristics which differentiate this species from other yeastlike pathogens.

Simplified techniques for identifying foodborne yeasts

Four problematic areas associated with the identification of foodborne yeasts are discussed. These consist of (1) the inability of conventional identification tests to recognize some common and important foodborne yeasts characterized by genomic differences (e.g., Saccharomyces cerevisiae, S. bayanus and S. pastorianus); (2) the delay in application of non-traditional identification methods such as DNA fingerprinting, chromosome karyotyping, protein electrophoretic patterns and fatty acid profiles for routine identification purposes; (3) the lack of commercially available manual or automated identification systems dedicated to the diagnosis of foodborne yeasts; and (4) the disregard for considering ecological frequency of yeasts in computerized probabilistic identification systems.