Res Microbiol, 2006, 157(7):684-692

Genomic fingerprinting of Burkholderia pseudomallei and B. mallei pathogens with DNA array based on interspecies sequence differences obtained by subtractive hybridization

The ability to rapidly and efficiently identify causative agents of dangerous human and animal diseases is a prerequisite to diagnosis, prophylaxis and therapy. Such identification systems can be developed based on DNA markers enabling differentiation between various bacterial strains. One source of these markers is genetic polymorphism. An efficient method for detecting the most stable polymorphisms without knowledge of genomic sequences is subtractive hybridization. In this work we report an approach to typing of Burkholderia pseudomallei and B. mallei that cause melioidosis and glanders, respectively. Typing is based on hybridization of bacterial genomes with a DNA array of genomic markers obtained using subtractive hybridization. The array comprised 55 DNA fragments which distinguished the genomes of B. pseudomallei C-141 and B. mallei C-5 strains, and it was used to test 28 radioactively labeled B. pseudomallei strains and 8 B. mallei strains. Each strain was characterized by a specific hybridization pattern, and the results were analyzed using cluster analysis. 18 patterns specific to B. pseudomallei and 6 patterns specific to B. mallei were found to be unique. The data allowed us to differentiate most studied B. pseudomallei variants from one another and from B. mallei strains. It was concluded that DNA markers obtained by subtractive hybridization can be potentially useful for molecular typing of B. pseudomallei and B. mallei strains, as well as for their molecular diagnosis. The method reported can be easily adapted for use both with DNA arrays and DNA microarrays with fluorescent probes. © 2006 Elsevier SAS. All rights reserved.

Fushan A, Monastyrskaya G, Abaev I, Sverdlov E

IBCH: 828
Ссылка на статью в журнале: http://linkinghub.elsevier.com/retrieve/pii/S0923250806000623
Кол-во цитирований на 11.2023: 2
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