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Rapid and Accurate Detection of Gnomoniopsis smithogilvyi the Causal Agent of Chestnut Rot, through an Internally Controlled Multiplex PCR Assay

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posted on 2023-07-21, 04:00 authored by Matias Silva-Campos, Pavani Nadiminti, David Cahill
The fungus Gnomoniopsis smithogilvyi is a significant threat to the production of sweet chestnut (Castanea sativa) nuts in Australia and worldwide. The pathogen causes nut rot, which leads to substantial production losses. Early and accurate diagnosis of the disease is essential to delineate and implement control strategies. A specific and sensitive multiplex PCR was developed based on the amplification of three barcode sequences of G. smithogilvyi. The assay reliability was enhanced by including the amplification of a host gene as an internal control. Primers were thoroughly evaluated in silico before assessing them in vitro. Primer annealing temperature and concentration were optimised to enhance the assay sensitivity and specificity. The assay detection limit ranged between 0.1 and 1.0 pg (5 and 50 fg/μL) of genomic DNA per reaction. No cross-reactivity was observed with genomic DNA from closely and distantly related fungal species. We also characterised Australian G. smithogilvyi isolates phenotypically and genotypically and found significant differences in morphologic and virulence traits of the isolates. An understanding of the virulence of G. smithogilvyi and the availability of a reliable and accurate diagnostic technique will enable earlier detection of the pathogen, which will contribute to effective control strategies for the disease.

Funding

This research was jointly funded by Deakin University Faculty of Science, Engineering and Built Environment "Industry support scheme" and Premium Chestnuts Australia Co-operative Ltd and the APC was similarly funded.

History

Publication Date

2022-08-12

Journal

Pathogens

Volume

11

Issue

8

Article Number

907

Pagination

22p.

Publisher

Multidisciplinary Digital Publishing Institute

ISSN

2076-0817

Rights Statement

© 2022 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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