Detection and characterization of fungal infections of Ammophila arenaria (marram grass) roots by denaturing gradient gel electrophoresis of specifically amplified 18s rDNA

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Abstract
Marram grass (Ammophila arenaria L.), a sand-stabilizing plant species in coastal dune areas, is affected by a specific pathosystem thought to include both plant-pathogenic fungi and nematodes. To study the fungal component of this pathosystem, we developed a method for the cultivation-independent detection and characterization of fungi infecting plant roots based on denaturing gradient gel electrophoresis (DGGE) of specifically amplified DNA fragments coding for 18S rRNA (rDNA). A nested PCR strategy was employed to amplify a 569-bp region of the 18S rRNA gene, with the addition of a 36-bp GC clamp, from fungal isolates, from roots of test plants infected in the laboratory, and from field samples of marram grass roots from both healthy and degenerating stands from coastal dunes in The Netherlands. PCR products from fungal isolates were subjected to DGGE to examine the variation seen both between different fungal taxa and within a single species. DGGE of the 18S rDNA fragments could resolve species differences from fungi used in this study yet was unable to discriminate between strains of a single species. The 18S rRNA genes from 20 isolates of fungal species previously recovered from A. arenaria roots were cloned and partially sequenced to aid in the interpretation of DGGE data. DGGE patterns recovered from laboratory plants showed that this technique could reliably identify known plant-infecting fungi. Amplification products from field A. arenaria roots also were analyzed by DGGE, and the major bands were excised, reamplified, sequenced, and subjected to phylogenetic analysis. Some recovered 18S rDNA sequences allowed for phylogenetic placement to the genus level, whereas other sequences were not closely related to known fungal 18S rDNA sequences. The molecular data presented here reveal fungal diversity not detected in previous culture-based surveys.