|Lee, Ing Ming|
Submitted to: International Journal of Systematic and Evolutionary Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/27/2006
Publication Date: 8/1/2007
Citation: Wei, W., Davis, R.E., Lee, I., Zhao, Y. 2007. Computer-simulated RFLP analysis of 16S rRNA genes: Identification of 11 new phytoplasma groups. International Journal of Systematic and Evolutionary Microbiology. 57:1855-1867.
Interpretive Summary: Phytoplasmas are a large group of small bacteria that infect several hundred plant species, causing numerous diseases in economically important vegetable, cereal, fruit, ornamental, and forest crops worldwide. These bacteria lack a cell wall; they live inside nutrition-transporting vessels of infected plants and are spread from diseased to healthy plants by a specific group of insects called leafhoppers. 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. In the present study, we used computer programs to mimic the laboratory DNA fingerprinting procedures and rapidly generated digital DNA fingerprint patterns. With this method, we identified 11 new groups of phytoplasmas and significantly expanded the existing standard phytoplasma DNA fingerprint pattern types. The method and findings of this study will help phytoplasma researchers, plant doctors, and quarantine personnel to identify phytoplasmas quickly.
Technical Abstract: Phytoplasmas are cell wall-less bacteria that cause numerous plant diseases. Because no phytoplasma culture has been established in cell-free medium, they cannot be differentiated and classified by traditional methods that are applied to culturable prokaryotes. Over the past decade, establishment of a phytoplasma classification scheme based on 16S rDNA restriction fragment length polymorphism (RFLP) patterns made possible the accurate and reliable identification and classification of a wide range of phytoplasmas. In the present study, we expanded this classification scheme through the use of computer-simulated RFLP analysis, achieving rapid differentiation and classification of phytoplasmas. Over 800 publicly available phytoplasma 16S rRNA gene sequences were aligned using the ClustalW algorithm, and the aligned 1.25 kb fragments were exported to software pDRAW32 for in silico restriction digestion and virtual gel plotting. Based on distinctive, virtual RFLP patterns and calculated similarity coefficients, phytoplasma strains were classified into 29 groups and more than 100 subgroups. The results included the classification of more than 250 previously unclassified phytoplasmas and delineation of 11 new phytoplasma groups representing no less than eight new, putative phytoplasma species.