Bioinformatics strategies for microbial forensics
W. SCHNEIDER (1), R. Verma (2), A. Stobbe (2), J. Daniels (2), A. Espindola (2), T. Blagden (2), J. Fletcher (2), F. M. Ochoa-Corona (2), C. Garzon (2), U. Melcher (2). (1) USDA ARS, Fort Detrick, MD, U.S.A.; (2) National Institute for Microbial Forensics & Food and Agricultural Biosecurity, Oklahoma State University, Stillwater, OK, U.S.A.
Deep sequencing (or next-generation sequencing) has altered the molecular biology landscape in many ways, including the development of the field of metagenomics. Not surprisingly, deep sequencing using metagenomics principles has been applied to diagnostics and microbial forensics. The unique DNA signatures of microbial pathogens lend themselves to forensic analysis of sequences. However, translating the effective mechanisms in place for human microbial agents (e.g. Pulsenet, a database of human foodborne pathogens) to plant pathogens is not a trivial task. Relatively few plant pathogens have complete genome sequences available, and very few plant pathogens have the necessary population sequences to develop significantly useful forensic sequence-based databases. In addition, plant diagnostic clinics and networks lack the monetary and computer resources dedicated to microbial forensics in the human health arena. A diagnostic bioinformatic process, termed E-probe Diagnostic Nucleic acids Analysis (EDNA) was developed to address some of these problems, by lessening the need for input sequence and limiting the amount of memory intensive analyses. <i>In silico</i> simulations and <i>in planta</i> analyses indicated that EDNA was capable of strain typing viruses.
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