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RNA and protein biomarkers for detecting enhanced metabolic resistance to herbicides mesosulfuron-methyl and fenoxaprop-ethyl in black-grass (Alopecurus myosuroides)

Lookup NU author(s): Claudia Lowe, Dr Nawaporn OnkokesungORCiD, Dr Alina Goldberg Cavalleri, Emeritus Professor Robert Edwards

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. BACKGROUND: The evolution of non-target site resistance (NTSR) to herbicides leads to a significant reduction in herbicide control of agricultural weed species. Detecting NTSR in weed populations prior to herbicide treatment would provide valuable information for effective weed control. While not all NTSR mechanisms have been fully identified, enhanced metabolic resistance (EMR) is one of the better studied, conferring tolerance through increased herbicide detoxification. Confirming EMR towards specific herbicides conventionally involves detecting metabolites of the active herbicide molecule in planta, but this approach is time-consuming and requires access to well-equipped laboratories. RESULTS: In this study, we explored the potential of using molecular biomarkers to detect EMR before herbicide treatment in black-grass (Alopecurus myosuroides). We tested the reliability of selected biomarkers to predict EMR and survival after herbicide treatments in both reference and 27 field-derived black-grass populations collected from sites across the UK. The combined analysis of the constitutive expression of biomarkers and metabolism studies confirmed three proteins, namely, AmGSTF1, AmGSTU2 and AmOPR1, as differential biomarkers of EMR toward the herbicides fenoxaprop-ethyl and mesosulfuron in black-grass. CONCLUSION: Our findings demonstrate that there is potential to use molecular biomarkers to detect EMR toward specific herbicides in black-grass without reference to metabolism analysis. However, biomarker development must include testing at both transcript and protein levels in order to be reliable indicators of resistance. This work is a first step towards more robust resistance biomarker development, which could be expanded into other herbicide chemistries for on-farm testing and monitoring EMR in uncharacterised black-grass populations. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.


Publication metadata

Author(s): Lowe C, Onkokesung N, Goldberg A, Beffa R, Neve P, Edwards R, Comont D

Publication type: Article

Publication status: Published

Journal: Pest Management Science

Year: 2024

Pages: Epub ahead of print

Online publication date: 20/02/2024

Acceptance date: 28/12/2023

Date deposited: 11/03/2024

ISSN (print): 1526-498X

ISSN (electronic): 1526-4998

Publisher: John Wiley and Sons Ltd

URL: https://doi.org/10.1002/ps.7960

DOI: 10.1002/ps.7960

Data Access Statement: Data will be openly available in a public repository that issues datasets with DOIs (Rothamsted Repository) after successful publication.


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Funding

Funder referenceFunder name
Bayer, AG
BB/L001489/1
BB/M016420/1
BBSRC
Agriculture and Horticulture Development Board
BB/X010953/1
RD-2012-3807

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