Multilocus Sequence Typing: a Molecular Typing Method with High Discriminatory Power for Identification of Candida Albicans Strains in Epidemiological Studies

Message:
Abstract:
Candida spp. are ubiquitous yeasts commonly. Those are commensally and opportunist pathogens in humans. Candidiasis in immunocompromised patients and patients with severe underlying diseases or critical illnesses need aggressive diagnosis or treatment procedures. Candida albicans (C. albicans) is the most frequently isolated species. For prevention of nosocomial infections caused by C. albicans، molecular characterization of the isolates is essential to understand the epidemiology of the infections and for tailoring prevention strategies. During the past two decades، different typing methods described for molecular characterization of C. albicans. Multilocus sequence typing (MLST)، as one of these methods، is available for the development of global epidemiological studies. MLST relies on DNA sequence analysis of nucleotide polymorphisms within 7 housekeeping genes with highly discriminating power. For each locus، the different sequences are assigned as distinct alleles، and for each isolate، the alleles at each of the sequenced loci define a sequence type (ST). In this context، global internet-linked databases are now available at www. mlst. net and allow results from strains typed anywhere in the world to be integrated and managed. Analysis of a large number of C. albicans isolates from various hosts and clinical situations carried out with MLST method can provide important insights into the epidemiology of hospital-acquired Candida infections as well as the C. albicans population. With an increased use of this technique، worldwide epidemiological studies will be facilitated and should reveal the patterns of transmission and evolution of C. albicans and help to evaluate the genetic diversity and dynamics of C. albicans population.
Language:
Persian
Published:
Journal of Mazandaran University of Medical Sciences, Volume:23 Issue: 106, 2013
Pages:
161 to 174
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