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Non-albicans Candida species and other rare yeasts have emerged as major opportunistic pathogens in fungal infections. Identification of opportunistic yeasts in developing countries is mainly performed by phenotypic assay, which are time-consuming and prone to errors. The aim of the present study was to evaluate PCR-RFLP as a routinely used identification technique for the most clinically important Candida species in Iran and make a comparison with a novel multiplex PCR, called 21-plex PCR. One hundred and seventy-three yeast isolates from clinical sources were selected and identified with sequence analysis of the D1/D2 domains of rDNA (LSU rDNA) sequencing as the gold standard method. The results were compared with those obtained by PCR-RFLP using MspI restriction enzyme and the 21-plex PCR. PCR-RFLP correctly identified 93.4% of common pathogenic Candida species (C. albicans, C. glabrata, C. parapsilosis, C. tropicalis, and P. kudriavsevii (=?C. krusei)) and was able to identify 45.5% of isolates of the uncommon yeast species compared to the D1/D2 rDNA sequencing. Compared with PCR-RFLP, all common Candida species and 72.7% of uncommon yeast species were correctly identified by the 21-plex PCR. The application of the 21-plex PCR assay as a non-sequence-based molecular method for the identification of common and rare yeasts can reduce turnaround time and costs for the identification of clinically important yeasts and can be applied in resource-limited settings.
相似文献BReast CAncer gene 1 (BRCA1)—a tumor suppressor gene plays an important role in the DNA repair mechanism. Several BRCA1 variants perturb its structure and function, including synonymous and nonsynonymous single nucleotide polymorphisms (SNPs). In the present study, we performed in-silico analyses of nonsynonymous SNPs (nsSNPs) of the BRCA1 gene. In total, 122 nsSNPs were retrieved from the NCBI SNP database and in-silico analyses were performed using computational prediction tools: SIFT, PROVEAN, Mutation Taster, PolyPhen-2, MutPred, and ConSurf. Of these tools, SIFT, PROVEAN, and Mutation Taster predicted 61 out of 122 nsSNPs as “damaging”, based on structural homology analysis. PolyPhen-2 classified 22 nsSNPs as “probably damaging”. These nsSNPs were further analyzed by MutPred to predict basic molecular mechanisms of amino acid alteration. ConSurf analysis predicted eleven conserved amino acid residues with structural and functional consequences. We identified five amino acid residues in the RING finger domain (L22, C39, H41, C44, and C47) and two in the BRCT domain (P1771 and I1707) with the potential to deter the BRCA1 protein function. This study provides insights into the effect of nsSNPs and amino acid substitutions in BRCA1.
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