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Bioinformatics Advance Access originally published online on October 26, 2006
Bioinformatics 2007 23(1):5-13; doi:10.1093/bioinformatics/btl549
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Oligonucleotide fingerprint identification for microarray-based pathogen diagnostic assays

Waibhav Tembe , Nela Zavaljevski , Elizabeth Bode 1, Catherine Chase 1, Jeanne Geyer 1, Leonard Wasieloski 1, Gary Benson 2 and Jaques Reifman *

Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD Boston, MA, USA
1 Diagnostic Systems Division, US Army Medical Research Institute of Infectious Diseases, Ft. Detrick, MD Boston, MA, USA
2 Departments of Biology and Computer Science, Boston University Boston, MA, USA

*To whom correspondence should be addressed.

Motivation: Advances in DNA microarray technology and computational methods have unlocked new opportunities to identify ‘DNA fingerprints’, i.e. oligonucleotide sequences that uniquely identify a specific genome. We present an integrated approach for the computational identification of DNA fingerprints for design of microarray-based pathogen diagnostic assays. We provide a quantifiable definition of a DNA fingerprint stated both from a computational as well as an experimental point of view, and the analytical proof that all in silico fingerprints satisfying the stated definition are found using our approach.

Results: The presented computational approach is implemented in an integrated high-performance computing (HPC) software tool for oligonucleotide fingerprint identification termed TOFI. We employed TOFI to identify in silico DNA fingerprints for several bacteria and plasmid sequences, which were then experimentally evaluated as potential probes for microarray-based diagnostic assays. Results and analysis of approximately 150 in silico DNA fingerprints for Yersinia pestis and 250 fingerprints for Francisella tularensis are presented.

Availability: The implemented algorithm is available upon request.

Contact: jaques.reifman{at}us.army.mil.

Received on June 15, 2006; revised on October 18, 2006; accepted on October 21, 2006

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