A high-throughput pipeline for designing microarray-based pathogen diagnostic assays

Vijaya Satya, Ravi; Zavaljevski, Nela; Kumar, Kamal; Reifman, Jaques

doi:10.1186/1471-2105-9-185

A high-throughput pipeline for designing microarray-based pathogen diagnostic assays

Journal Article · Thu Apr 10 00:00:00 EDT 2008 · BMC Bioinformatics

DOI:https://doi.org/10.1186/1471-2105-9-185· OSTI ID:1626352

Vijaya Satya, Ravi ^[1]; Zavaljevski, Nela ^[2]; Kumar, Kamal ^[2]; Reifman, Jaques ^[2]

US Army Medical Research and Materiel Command, Fort Detrick, MD (United States). Telemedicine and Advanced Technology Research Center. Biotechnology HPC Software Applications Inst.; DOE/OSTI
US Army Medical Research and Materiel Command, Fort Detrick, MD (United States). Telemedicine and Advanced Technology Research Center. Biotechnology HPC Software Applications Inst.

fingerprints for microarray-based pathogen diagnostic assays. The oligonucleotide fingerprints, or DNA microarray probes, are designed for identifying target organisms in environmental or clinical samples. The design process is implemented in a high-performance computing software pipeline that incorporates major algorithmic improvements over a previous version to both reduce computation time and improve specificity assessment. Results: The algorithmic improvements result in significant reduction in runtimes, with the updated pipeline being nearly up to five-times faster than the previous version. The improvements in specificity assessment, based on multiple specificity criteria, result in robust and consistent evaluation of cross-hybridization with nontarget sequences. In addition, the multiple criteria provide finer control on the number of resulting fingerprints, which helps in obtaining a larger number of fingerprints with high specificity. Simulation tests for Francisella tularensis and Yersinia pestis, using a well-established hybridization model to estimate cross-hybridization with nontarget sequences, show that the improved specificity criteria yield a larger number of fingerprints as compared to using a single specificity criterion. Conclusion: The faster runtimes, achieved as the result of algorithmic improvements, are critical for extending the pipeline to process multiple target genomes. The larger numbers of identified fingerprints, obtained by considering broader specificity criteria, are essential for designing probes for hard-to-distinguish target sequences.

View Accepted Manuscript (DOE)

Research Organization:: USDOE Joint Genome Institute (JGI), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

OSTI ID:: 1626352

Journal Information:: BMC Bioinformatics, Journal Name: BMC Bioinformatics Journal Issue: 1 Vol. 9; ISSN 1471-2105

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: United States

Language:: English

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ORMA: a tool for identification of species-specific variations in 16S rRNA gene and oligonucleotides design Severgnini, Marco; Cremonesi, Paola; Consolandi, Clarissa Nucleic Acids Research, Vol. 37, Issue 16 https://doi.org/10.1093/nar/gkp499	journal	June 2009
A high-throughput pipeline for the design of real-time PCR signatures Vijaya Satya, Ravi; Kumar, Kamal; Zavaljevski, Nela BMC Bioinformatics, Vol. 11, Issue 1 https://doi.org/10.1186/1471-2105-11-340	journal	June 2010
A microbial detection array (MDA) for viral and bacterial detection Gardner, Shea N.; Jaing, Crystal J.; McLoughlin, Kevin S. BMC Genomics, Vol. 11, Issue 1 https://doi.org/10.1186/1471-2164-11-668	journal	January 2010
In silico microarray probe design for diagnosis of multiple pathogens Vijaya Satya, Ravi; Zavaljevski, Nela; Kumar, Kamal BMC Genomics, Vol. 9, Issue 1 https://doi.org/10.1186/1471-2164-9-496	journal	October 2008
Rapid identification of bacterial pathogens using a PCR- and microarray-based assay Järvinen, Anna-Kaarina; Laakso, Sanna; Piiparinen, Pasi BMC Microbiology, Vol. 9, Issue 1 https://doi.org/10.1186/1471-2180-9-161	journal	August 2009
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Accessible High-Throughput Virtual Screening Molecular Docking Software for Students and Educators Jacob, Reed B.; Andersen, Tim; McDougal, Owen M. PLoS Computational Biology, Vol. 8, Issue 5 https://doi.org/10.1371/journal.pcbi.1002499	journal	May 2012

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