Abstract:
Identification of Candida species has become more important because of an increase in infections
caused by species other than Candida albicans, including species innately resistant to azole antifungal
drugs. This study was done to compare the phenotypic identification of clinically important yeast
species (using API 20 C AUX), with emphasis on poorly identifiable species, with rDNA sequence
based identification.
Clinical specimens from different sources including infected wounds, stool, urine, vaginal swabs and
oral swabs were cultured directly. Suspected Yeast were identified by gram stain, germ tube test and
API 20CAUX. The Internal Transcribed Spacers of the rDNA gene complex were amplified with
fungal universal primers and partial sequences were obtained. Sequence data were used to identify the
clinical
isolates
up
to
the
species
level
using
the
CBS
yeast
database
(http://www.cbs.knaw.nl/yeast/BioloMICSID.aspx). In addition to the DNA identification, the sugar
assimilation results of the API system were used to obtain additional phenotypic identification using
the polyphasic identification system of CBS yeast database. Twenty eight poorly identified isolates
were sequenced using primer ITS4, and sequences data were then used to search for sequence
homology in the CBS.
Using API 20 C AUX system, 92.6% of all strains were well identified (i.e. with high level of
identification) up-to-the species level and 7.4% of the isolates were poorly identified. DNA
sequencing resulted in excellent identification (≥ 98% homology) with most of the tested isolated.
Three yeast isolates had very low sequence homology (< 20%), which might represent novel new
yeast species.The study concluded that rDNA sequencing for yeast identification appeared to be the useful tool for
clinical microbiological laboratories for the identification of several yeast species which cannot be
.identified by common phenotypic methods such as API 20C AUX
