Asian Journal of Microbiology, Biotechnology & Environmental Sciences Paper

DNA SEQUENCE-BASED IDENTIFICATION OF POORLY IDENTIFIABLE YEAST SPECIES IN HAFAR ALBATIN AREA, SAUDI ARABIA

ELSHEIKH.B.KHIDIR, ABDALLA.O.AHMED, MUTAZ.F.SAAD AND HUMODI.A.SAEED

Abstract

The identification of Yeast species has become more important because of an increase in infections by species other than Candida albicans, which were resistant to azole antifungal drugs. This study was carried out to study the phenotypic identification of isolated yeast species using API 20 C AUX, with emphasis on poorly identifiable species and compare it with rDNA sequence based identification. Clinical specimens were cultured directly from different specimens including infected wounds, stool, urine, vaginal swabs and oral swabs. One hundred and fifty yeasts were recovered and identified by gram stain, germ tube test and API. Twenty eight (28) isolates with high score of identification were selected from all isolated yeast species for the DNA-based identification. DNA was extracted from selected isolates, and then sequenced using primer ITS4, and sequences data were then used to study the sequence homology in the CBS yeast database (http://www.cbs.knaw.nl/yeast/BioloMICSID.aspx). Using API 20 C AUX system, 92.6% of all strains were well identified with high level of identification up to the species level and 7.4% of the isolates were poorly identified. DNA sequencing identification showed excellent identification (≥ 98% homology) with most of the isolated species. Three yeast isolates showed very low sequence homology (< 20%), which might represent novel new yeast species. In this study, the identification was reached in 139 (92.6%) of the isolates, and in only 11 (7.4%) the API 20 C AUX level was of low discrimination and additional tests were needed to improve the quality of identification. This rate of identification was reported in previous studies. Most of the isolates were identified as C. albicans (34.6%), followed by other non- C. albicans species and some other yeast species. This result was in agreement to many reports that showed that C. albicans was isolated in similar frequency from clinical specimens. A wide range of different less common species of Candida and other yeast species (n=11) were identified by API with high levels of identification (i.e. excellent very good or good). Surprisingly, the ITS sequence of these isolates showed either perfect homology with un-related yeast species or no homology at all. These finding revealed failures of API 20 C AUX in identifying the uncommon yeast species and the possibility of the presence of un-known yeast species colonizing the studied population. As far as we know, this the first study to be done on yeast population from this region.