Location: Foreign Disease-Weed Science ResearchTitle: Insect E-probe Diagnostic Nucleic acid Analysis (EDNA): the application of a novel bioinformatic tool to detection of vectors and pathogens in individual insect and simulated insect trap metagenomes
|Stone, Andrew - Andy|
|ANDREASON, SHARON - Oklahoma State University|
|DANIELS, JON - Pennsylvania State University|
|OCHOA CORONA, FRANCISCO - Oklahoma State University|
|WAYADANDE, ASTRI - Oklahoma State University|
Submitted to: Phytopathology
Publication Type: Abstract Only
Publication Acceptance Date: 3/14/2015
Publication Date: 11/1/2015
Citation: Schneider, W.L., Stone, A.L., Sherman, D.J., Wight-Malapi, M., Andreason, S.A., Daniels, J., Ochoa Corona, F., Crouch, J., Wayadande, A. 2015. Insect E-probe Diagnostic Nucleic acid Analysis (EDNA): the application of a novel bioinformatic tool to detection of vectors and pathogens in individual insect and simulated insect trap metagenomes. Phytopathology. 105: S4:124.
Technical Abstract: Plant pathogen detection takes many forms. In simple cases, researchers are attempting to detect a known pathogen from a known host utilizing targeted nucleic acid or antigenic assays. However, in more complex scenarios researchers may not know the identity of a pathogen, or they may need to screen for a wide array of pathogens from a single sample. Metagenomics represents a possible broad range diagnostic approach, with next generation sequencing generating a comprehensive profile of all organisms in a given nucleic acid sample. However, the vast amount of data gathered makes metagenomic analysis computationally problematic. EDNA is a bioinformatic tool that greatly reduces the amount of computational work in metagenomic data diagnoses. A prime target for EDNA may be insect traps, which represent diverse samples that may include vectors of a wide array of viral and bacterial pathogens. Currently insects from traps are analyzed morphologically and tested for related pathogens individually. To test if this process could be simplified, EDNA was applied to the detection of vectors and plant pathogens in individual insect and simulated trap samples. In proof of concept experiments EDNA identified insect vectors from 454 data, while vectors plus bacterial pathogens and viral pathogens were identified using the Illumina platform. These data indicate that EDNA analysis of metagenomes may provide a viable means for screening insect trap samples for vectors and pathogens.