A loop-mediated isothermal amplification (LAMP) assay for rapid and specific detection of airborne inoculum of Uromyces betae (sugar beet rust)

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Kaczmarek, A. M., King, K. M., West, J. S., Stevens, M., Sparkes, D. and Dickinson, M. 2019. A loop-mediated isothermal amplification (LAMP) assay for rapid and specific detection of airborne inoculum of Uromyces betae (sugar beet rust). Plant Disease.

AuthorsKaczmarek, A. M., King, K. M., West, J. S., Stevens, M., Sparkes, D. and Dickinson, M.
Abstract

Sugar beet rust disease (causal agent Uromyces betae) represents a serious threat to worldwide sugar beet (Beta vulgaris) crops, causing yield losses of up to 10% in the UK. Currently, the disease is managed mainly by application of fungicides after rust disease symptoms appear. Development of a future forecasting system, incorporating data on environmental factors and U. betae inoculum levels, would enable better disease control by more targeted application of fungicides. In this study, we develop a first molecular diagnostic, targeted to cytochrome b DNA sequences and based on loop-mediated isothermal amplification (LAMP) technology, for rapid (<30 mins) and specific detection of U. betae. The new assay only detected U. betae strains (collected from across eastern England, the main sugar beet growing region in the UK); it did not detect other closely related pathogens (e.g. Puccinia sp., U. fabae) or others that are commonly found on sugar beet (Cercospora beticola, Erysiphae betae, Ramularia beticola). The assay could consistently detect down to small amounts of U. betae DNA (10 pg). Application of the new LAMP diagnostic to air spore tape samples collected between mid June – mid September from a single UK sugar beet field site revealed differences in temporal patterns of pathogen inoculum between the 2015 and 2016 seasons. The described LAMP assay could now be used as a component of a future automated inoculum-based forecasting system, enabling more targeted control of sugar beet rust disease.

Keywordsairborne inoculum
crop protection
diagnostics
disease 1 forecasting
pathogen detection
Year of Publication2019
JournalPlant Disease
Digital Object Identifier (DOI)doi:10.1094/PDIS-02-18-0337-RE
Publisher's versionpdis-02-18-0337-re.pdf
Other fileAgata_rustmanuscript240517.docx
Fig 1.pdf
Fig 2.pdf
Fig. 3. Spores per day.pdf
Publication dates
Online29 Aug 2018
Copyright licenseCC BY
PublisherAmer Phytopathological Soc
ISSN0191-2917

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