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Microbial Fingerprinting Chip and Automated Analysis

$264,257R21FY2002EBNIH

Battelle Pacific Northwest Laboratories, Richland WA

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Abstract

DESCRIPTION (provided by applicant): DNA fingerprinting provides the capability to identify and genetically discriminate between closely related strains of microorganisms, which is required for forensic identification and tracking of disseminated bio-agents or pathogens (e.g., Bacillus anthracis). However, the development and application of advanced diagnostic techniques for the identification and characterization of microorganisms continues to be limited by the absence of instrumentation and methods that are (1) capable of discriminating between closely related microorganisms, (2) rapid, easy-to-use, and conducive to automation, (3) capable of producing statistically rigorous data with relative ease, and (4) highly reproducible. The continued inability of forensic scientists to locate the geological or institutional origin of B. anthracis released into the U.S. Postal Service highlights the continued need for a rapid, automated, objective, and high-resolution diagnostic system for microorganisms. The objective of this project is therefore to demonstrate a universal DNA fingerprinting microarray and statistically based data analysis algorithms for the forensic identification and diagnosis of B. anthracis and/or near-neighbors within the B. cereus complex. The universal DNA fingerprinting microarray proposed here utilizes the power of "genome scanning" and "sequencing by hybridization" to interrogate a larger proportion of the genome than can be accessed with current PCR- or gel-based methods. In contrast to PCR or gene-probe methods, the universal fingerprinting microarray may further be capable of identifying "emerging" or otherwise "unknown" microorganisms for which specific gene sequences are not available or known. Because the method and DNA chip is "universal", it may be applicable for the identification of other microorganism, as demonstrated in our preliminary studies with Salmonella, Xanthomonas and E. coli pathogens.

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Microbial Fingerprinting Chip and Automated Analysis · GrantIndex