Evolution of generalist resistance to herbicide mixtures reveals a trade-off in resistance management

Intense selection by pesticides and antibiotics has resulted in a global epidemic of evolved resistance. In agriculture and medicine, using mixtures of compounds from different classes is widely accepted as optimal resistance management. However, this strategy may promote the evolution of more generalist resistance mechanisms. Here we test this hypothesis at a national scale in an economically important agricultural weed: blackgrass (Alopecurus myosuroides), for which herbicide resistance is a major economic issue. Our results reveal that greater use of herbicide mixtures is associated with lower levels of specialist resistance mechanisms, but higher levels of a generalist mechanism implicated in enhanced metabolism of herbicides with diverse modes of action. Our results indicate a potential evolutionary trade-off in resistance management, whereby attempts to reduce selection for specialist resistance traits may promote the evolution of generalist resistance. We contend that where specialist and generalist resistance mechanisms co-occur, similar trade-offs will be evident, calling into question the ubiquity of resistance management based on mixtures and combination therapies.


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Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.  (3), 1584-1594). For herbicide experiments, replicate pots were blocked over three glasshouse compartments, with the position of pots within each compartment determined using a randomised alpha design. Samples for protein analysis were immediately flash-frozen in liquid N and stored at -80C. Samples for pyrosequencing were air-dried before analysis D.Comont and H.Hicks led the field monitoring and collection of seed populations and farm management data. D.Comont, L.Crook, and R.Hull performed the glasshouse experiments. C.Lowe performed the pyrosequencing. D.Comont performed protein extractions, and N.Onkokesung performed the quantification of AmGSTF1 protein concentration. Blackgrass abundance was recorded in contiguous 20x20m quadrats across each field, while seeds were collected from multiple plants across 10 locations per field, sampled from a circumference of approximately 5-10m. Herbicide spraying was performed using a custom-built track sprayer with a Teejet 110015VK nozzle. Tissue for protein and pyrosequencing analysis was collected by excising leaf material using scissors. Pyrosequencing results were taken using a Pyromark Q96 MD pyrosequencer, while protein concentration was determined using a microplate reader (iMark, BioRad).
Analyses are based on a network of 132 field populations of blackgrass, distributed across Eastern England from Hertfordshire in the South to Yorkshire in the North. Seeds were collected at a single pre-harvest time-point from each field, between July -early August 2014. Collection at this time ensured that only mature seed heads were sampled. All subsequent analyses were performed on plants grown from these seed populations. Glasshouse assays were timed to coincide with times of blackgrass vegetative growth in-field. In particular, herbicide assays were conducted over October 2014 -May 2015. Undertaking experimentation at this time ensures that ambient temperatures and light levels can be controlled more appropriately. Experimental durations were based on those determined from previous experimentation in this species (see e.g. Davies and Neve 2017, Weed research 57: 323-332, and Comont et al. New Phytologist. 223(3), 1584-1594), and represented 6-7 days pre-germination, 2-3 weeks growth to the three-leaf stage, and 3 weeks post spraying.
Data were excluded from farms from which we were unable to obtain appropriate field management data. We made repeated attempts to obtain all such data.
This was predominantly an observational study based on epidemiological associations between field populations and management histories. Individual experiments were not repeated, however the combined phenotypic resistance data is based on three separate glasshouse assays testing a different herbicide each time, with over 40,000 plants phenotyped in total. In all cases, appropriate positive and negative controls were used, such as using standard populations of known phenotype to validate results, and appropriate replication was used across all experiments. All population-level phenotypes were assessed from multiple, replicated individuals, for example with >100 individuals screened per population per herbicide.
Seeds from across a single field were designated as a single population. Position of plants grown from these seed populations in the glasshouse was randomised using an alpha design Observational study: we did not assign to groups. Each population was assigned a unique but uninformative numerical code throughout analysis Seeds were collected from Winter wheat fields pre-harvest in summer 2014 at the time of Blackgrass seed maturity and shedding (July -early August) Fields spanned a range of locations over Eastern England, from Oxfordshire/Hertfordshire in the South, to Yorkshire in the North Permission was sought and granted from individual land owners before accessing any private land, and before the collection and analysis of seed populations.
All care was taken to avoid any damage to the crop.