Nucleic Acids Research, 2003, Vol. 31, No. 2 779-789
© 2003 Oxford University Press
Fingerprinting of prokaryotic 16S rRNA genes using oligodeoxyribonucleotide microarrays and virtual hybridization
1 Life Sciences Division, Oak Ridge National Laboratory, Building 4500-S, MS 6123, Bethel Valley Road, PO Box 2008, Oak Ridge, TN 37831, USA, 2 Laboratorio de Tecnología del DNA, Escuela Nacional de Ciencias Biológicas, IPN, Pról. Carpio y Plan de Ayala S/n, 11340, México, D.F., Mexico and 3 The Center for Environmental Biotechnology, University of Tennessee, 676 Dabney Hall, Knoxville, TN 37996-1605, USA
*To whom correspondence should be addressed. Tel/Fax: +52 55 729 6300; Email: romaldodr{at}hotmail.com
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
An oligonucleotide microarray hybridization system to differentiate microbial species was designed and tested. Seven microbial species were studied, including one Bacillus and six Pseudomonas strains. DNA sequences near the 5' end of 16S rRNA genes were aligned and two contiguous regions of high variability, flanked by highly conserved sequences, were found. The conserved sequences were used to design PCR primers which efficiently amplified these polymorphic regions from all seven species. The amplicon sequences were used to design 88 9mer hybridization probes which were arrayed onto glass slides. Single-stranded, fluorescence-tagged PCR products were hybridized to the microarrays at 15°C. The experimental results were compared with the 
G° values for all matched and mismatched duplexes possible between the synthetic probes and the 16S target sequences of the seven test species, calculated using a ‘virtual hybridization’ software program. Although the observed hybridization patterns differed significantly from patterns predicted solely on the basis of perfect sequence matches, a unique hybridization fingerprint was obtained for each of the species, including closely related Pseudomonas species, and there was a reasonable correlation between the intensity of observed hybridization signals and the calculated G° values. The results suggest that both perfect and mismatched pairings can contribute to microbial identification by hybridization fingerprinting.
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