Skip to main content
ARS Home » Research » Publications at this Location » Publication #220096
Title: Automated RFLP pattern comparison and similarity coefficient calculation for rapid delineation of new and distinct phytoplasma 16S rDNA subgroup lineages

Author
item WEI, WEI - LIAONING CHINA
item Lee, Ing Ming
item Davis, Robert
item SUO, XIAOBING - HERNDON VIRGINIA
item Zhao, Yan

Submitted to: International Journal of Systematic and Evolutionary Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/21/2008
Publication Date: 10/1/2008
Citation: Wei, W., Lee, I., Davis, R.E., Suo, X., Zhao, Y. 2008. Automated RFLP pattern comparison and similarity coefficient calculation for rapid delineation of new and distinct phytoplasma 16S rDNA subgroup lineages. International Journal of Systematic and Evolutionary Microbiology. 58:2368-2377.

Interpretive Summary: Phytoplasmas are a large group of small bacteria that infect several hundred plant species, causing numerous diseases in economically important crops worldwide. These bacteria live inside nutrition-transporting vessels of infected plants and are spread from diseased to healthy plants by a specific group of insects called leafhoppers. In adaptation to their broad range of plant and insect hosts, phytoplasmas have evolved to give rise to widely divergent groups. Since phytoplasmas cannot be cultivated in the laboratory, DNA fingerprinting is the best way to distinguish them from one another. Conventional DNA fingerprinting involves several complicated and expensive laboratory procedures. Recently, we used computer programs to mimic the laboratory DNA fingerprinting procedures and quickly identified a significant number of new phytoplasma groups. In the present study, we have developed new software, further streamlining the computer-aided phytoplasma identification process. With this new software, several novel phytoplasma DNA fingerprint pattern types (biomarkers) are discovered, and distinct phytoplasma lineages bearing the new biomarkers are identified. The method and findings of this study will help phytoplasma researchers, plant doctors, and quarantine personnel to identify phytoplasmas more efficiently.

Technical Abstract: Phytoplasmas are insect-borne, phloem-inhabiting, cell wall-less bacteria that cause numerous diseases in several hundred plant species. In adaptation to transkingdom parasitism in diverse plant and insect hosts, phytoplasma evolution has given rise to widely divergent lineages. Since phytoplasmas cannot be cultured in a cell-free medium, measurable phenotypic characters suitable for conventional microbial classification are mostly inaccessible. Currently, phytoplasma differentiation and classification are mainly dependent on restriction fragment length polymorphism (RFLP) analysis of 16S rDNA sequences. Extending our recent efforts in exploitation of computer-simulated 16S rDNA RFLP analysis and virtual gel plotting for rapid classification of phytoplasmas, we have developed a program for automated RFLP pattern comparison and similarity coefficient calculation. This program streamlines virtual RFLP pattern analysis and has led to in silico delineation of new and distinct subgroup lineages in clover proliferation phytoplasma group.