Currentmolecular detectionmethods for the genus Phytophthora are specific to a fewkey species rather than thewhole genus and this is a recognized weakness of protocols for ecological studies and international plant healthlegislation. In the present study a molecular approach was developed to detect Phytophthora species in soil andwater samples using novel sets of genus-specific primers designed against the internal transcribed spacer (ITS)regions. Two different rDNA primer sets were tested: one assay amplified a long product including the ITS1, 5.8Sand ITS2 regions (LP) and the other a shorter product including the ITS1 only (SP). Both assays specificallyamplified products from Phytophthora species without cross-reaction with the related Pythium s. lato, howeverthe SP assay proved the more sensitive and reliable. The method was validated using woodland soil and streamwater fromInvergowrie, Scotland. On-site use of a knapsack sprayer and in-line water filters provedmore rapidand effective than centrifugation at sampling Phytophthora propagules. A total of 15 different Phytophthoraphylotypes were identified which clustered within the reported ITS-clades 1, 2, 3, 6, 7 and 8. The range andtype of the sequences detected varied from sample to sample and up to three and five different Phytophthoraphylotypes were detected within a single sample of soil or water, respectively. The most frequently detectedsequences were related to members of ITS-clade 6 (i.e. P. gonapodyides-like). The new method proved veryeffective at discriminating multiple species in a given sample and can also detect as yet unknown species. Thereported primers and methods will prove valuable for ecological studies, biosecurity and commercial plant,soil or water (e.g. irrigation water) testing as well as the wider metagenomic sampling of this fascinatingcomponent of microbial pathogen diversity.

A molecular method to assess Phytophthora diversity in environmental samples

SCHENA L;
2012-01-01

Abstract

Currentmolecular detectionmethods for the genus Phytophthora are specific to a fewkey species rather than thewhole genus and this is a recognized weakness of protocols for ecological studies and international plant healthlegislation. In the present study a molecular approach was developed to detect Phytophthora species in soil andwater samples using novel sets of genus-specific primers designed against the internal transcribed spacer (ITS)regions. Two different rDNA primer sets were tested: one assay amplified a long product including the ITS1, 5.8Sand ITS2 regions (LP) and the other a shorter product including the ITS1 only (SP). Both assays specificallyamplified products from Phytophthora species without cross-reaction with the related Pythium s. lato, howeverthe SP assay proved the more sensitive and reliable. The method was validated using woodland soil and streamwater fromInvergowrie, Scotland. On-site use of a knapsack sprayer and in-line water filters provedmore rapidand effective than centrifugation at sampling Phytophthora propagules. A total of 15 different Phytophthoraphylotypes were identified which clustered within the reported ITS-clades 1, 2, 3, 6, 7 and 8. The range andtype of the sequences detected varied from sample to sample and up to three and five different Phytophthoraphylotypes were detected within a single sample of soil or water, respectively. The most frequently detectedsequences were related to members of ITS-clade 6 (i.e. P. gonapodyides-like). The new method proved veryeffective at discriminating multiple species in a given sample and can also detect as yet unknown species. Thereported primers and methods will prove valuable for ecological studies, biosecurity and commercial plant,soil or water (e.g. irrigation water) testing as well as the wider metagenomic sampling of this fascinatingcomponent of microbial pathogen diversity.
2012
Phytophthora spp.; Molecular detection; Metagenomic analyses; Genus-specific primers; Natural ecosystems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/6493
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