Literature DB >> 17463292

PCR-based strategy to detect and identify species of Phaeoacremonium causing grapevine diseases.

Angeles Aroca1, Rosa Raposo.   

Abstract

Species of Phaeoacremonium (especially Phaeoacremonium aleophilum) are associated with two severe diseases in grapevines, Petri disease in young plants and Esca disease in adult plants. Phaeoacremonium species grow slowly on culture medium, and it is difficult to identify these species on the basis of morphological characteristics. Primers Pm1 and Pm2 were designed in the ribosomal DNA internal transcribed spacer (ITS) regions ITS1 and ITS2, respectively. They yielded a single amplicon of 415 bp for nine species of Phaeoacremonium that may occur in grapevines. A nested PCR (using general fungal primers ITS1F/ITS4 in the primary reaction) was developed to detect Phaeoacremonium directly in grapevine wood. Molecular detection was more sensitive than the traditional method of culturing in growth medium was. Identification of Phaeoacremonium species was achieved by digesting the PCR-amplified fragment with the restriction enzymes BssKI, EcoO109I, and HhaI. It was possible to distinguish these species by their restriction fragment length polymorphism patterns, except for Phaeoacremonium viticola and Phaeoacremonium angustius, which had 100% similarity in their ITS region sequences. A species-specific PCR amplification of the partial beta-tubulin gene using the primer pair Pbr4_1/T1 and Pbr8/T1 was necessary to differentiate P. angustius from P. viticola, respectively. An easy and fast protocol was developed to detect and identify species of Phaeoacremonium in a few hours. Primers defined here can be used in a plant nursery sanitation program to produce plants free of Phaeoacremonium spp. Use of healthy grapevine plants in new plantations is the most effective measure to manage Petri disease.

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Year:  2007        PMID: 17463292      PMCID: PMC1892851          DOI: 10.1128/AEM.02176-06

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  6 in total

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2.  The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools.

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Authors:  K O'Donnell; E Cigelnik
Journal:  Mol Phylogenet Evol       Date:  1997-02       Impact factor: 4.286

4.  Two cases of subcutaneous infection due to Phaeoacremonium spp.

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Journal:  J Clin Microbiol       Date:  2003-03       Impact factor: 5.948

5.  ITS primers with enhanced specificity for basidiomycetes--application to the identification of mycorrhizae and rusts.

Authors:  M Gardes; T D Bruns
Journal:  Mol Ecol       Date:  1993-04       Impact factor: 6.185

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Authors:  Jan M van Niekerk; Pedro W Crous; J Z Ewald Groenewald; Paul H Fourie; Francois Halleen
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  6 in total
  7 in total

1.  Genera of phytopathogenic fungi: GOPHY 2.

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Journal:  Stud Mycol       Date:  2018-05-01       Impact factor: 16.097

2.  Real-time PCR detection of Phaeomoniella chlamydospora and Phaeoacremonium aleophilum.

Authors:  Maria Teresa Martín; Rebeca Cobos; Laura Martín; Lorena López-Enríquez
Journal:  Appl Environ Microbiol       Date:  2012-03-23       Impact factor: 4.792

Review 3.  Black Molds and Melanized Yeasts Pathogenic to Humans.

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Authors:  Bhanupratap R Vanga; Preeti Panda; Anish S Shah; Sarah Thompson; Rebecca H Woolley; Hayley J Ridgway; Dion C Mundy; Simon Bulman
Journal:  BMC Microbiol       Date:  2022-05-10       Impact factor: 4.465

5.  Novel Phaeoacremonium species associated with necrotic wood of Prunus trees.

Authors:  U Damm; L Mostert; P W Crous; P H Fourie
Journal:  Persoonia       Date:  2008-05-24       Impact factor: 11.051

6.  Exhibition of Local but Not Systemic Induced Phenolic Defenses in Vitis vinifera L. Affected by Brown Wood Streaking, Grapevine Leaf Stripe, and Apoplexy (Esca Complex).

Authors:  Piebiep Goufo; Ana C Marques; Isabel Cortez
Journal:  Plants (Basel)       Date:  2019-10-14

7.  Classification and Discrimination of Different Fungal Diseases of Three Infection Levels on Peaches Using Hyperspectral Reflectance Imaging Analysis.

Authors:  Ye Sun; Kangli Wei; Qiang Liu; Leiqing Pan; Kang Tu
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  7 in total

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