Literature DB >> 8931322

Genetic speciation of Candida isolates by arbitrarily primed polymerase chain reaction.

D Liu1, S Coloe, S L Jones, R Baird, J Pedersen.   

Abstract

Candida species are opportunistic human pathogens capable of causing a variety of clinical diseases. Rapid and precise identification of Candida to species level is essential for effective treatment and management strategies. Conventional diagnosis of candidiasis is sometimes slow and variable. By using a random primer 5'-ACGGGCCAGT-3' in arbitrarily primed polymerase chain reaction, seven common Candida species (i.e., C. albicans, C. guilliermondii, C. parapsilosis, C. krusei, C. lipolytica, C. tropicalis and C. (Torulopsis) glabrata) produced characteristic DNA band patterns, which enabled rapid determination to species level among them. Further analysis of the nucleotide sequences of Candida specific fragments should improve our understanding of the molecular structures and possible functions of the gene regions involved.

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Year:  1996        PMID: 8931322     DOI: 10.1111/j.1574-6968.1996.tb08551.x

Source DB:  PubMed          Journal:  FEMS Microbiol Lett        ISSN: 0378-1097            Impact factor:   2.742


  3 in total

1.  Usefulness of McRAPD for typing and importance of biofilm production in a case of nosocomial ventriculoperitoneal shunt infection caused by Candida lusitaniae.

Authors:  Petr Hamal; Juraj Hanzen; Frantisek Horn; Jitka Trtkova; Lenka Ruskova; Renata Vecerova; Filip Ruzicka; Anna Vollekova; Vladislav Raclavsky
Journal:  Folia Microbiol (Praha)       Date:  2011-09-06       Impact factor: 2.099

2.  Identification of Candida spp. by randomly amplified polymorphic DNA analysis and differentiation between Candida albicans and Candida dubliniensis by direct PCR methods.

Authors:  Consuelo Bautista-Muñoz; Xavier M Boldo; Lourdes Villa-Tanaca; César Hernández-Rodríguez
Journal:  J Clin Microbiol       Date:  2003-01       Impact factor: 5.948

3.  Performance of optimized McRAPD in identification of 9 yeast species frequently isolated from patient samples: potential for automation.

Authors:  Jitka Trtkova; Petr Pavlicek; Lenka Ruskova; Petr Hamal; Dagmar Koukalova; Vladislav Raclavsky
Journal:  BMC Microbiol       Date:  2009-11-10       Impact factor: 3.605

  3 in total

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