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Onkokesung, N.
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article
RNA and protein biomarkers for detecting enhanced metabolic resistance to herbicides mesosulfuron-methyl and fenoxaprop-ethyl in black-grass (Alopecurus myosuroides)
Abstract
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 explore the potential of using molecular biomarkers to detect EMR before herbicide treatment in black-grass (Alopecurus myosuroides).We test 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.