Resistance cost of a cytochrome P450 herbicide metabolism mechanism but not an ACCase target site mutation in a multiple resistant Lolium rigidum population

Evolution in action: plants resistant to herbicides

Modern herbicides make major contributions to global food production by easily removing weeds and substituting for destructive soil cultivation. However, persistent herbicide selection of huge weed numbers across vast areas can result in the rapid evolution of herbicide resistance. Herbicides target specific enzymes, and mutations are selected that confer resistance-endowing amino acid substitutions, decreasing herbicide binding. Where herbicides bind within an enzyme catalytic site very few mutations give resistance while conserving enzyme functionality. Where herbicides bind away from a catalytic site many resistance-endowing mutations may evolve. Increasingly, resistance evolves due to mechanisms limiting herbicide reaching target sites. Especially threatening are herbicide-degrading cytochrome P450 enzymes able to detoxify existing, new, and even herbicides yet to be discovered. Global weed species are accumulating resistance mechanisms, displaying multiple resistance across many herbicides and posing a great challenge to herbicide sustainability in world agriculture. Fascinating genetic issues associated with resistance evolution remain to be investigated, especially the possibility of herbicide stress unleashing epigenetic gene expression. Understanding resistance and building sustainable solutions to herbicide resistance evolution are necessary and worthy challenges.

Evolutionary-thinking in agricultural weed management

Agricultural weeds evolve in response to crop cultivation. Nevertheless, the central importance of evolutionary ecology for understanding weed invasion, persistence and management in agroecosystems is not widely acknowledged. This paper calls for more evolutionarily-enlightened weed management, in which management principles are informed by evolutionary biology to prevent or minimize weed adaptation and spread. As a first step, a greater knowledge of the extent, structure and significance of genetic variation within and between weed populations is required to fully assess the potential for weed adaptation. The evolution of resistance to herbicides is a classic example of weed adaptation. Even here, most research focuses on describing the physiological and molecular basis of resistance, rather than conducting studies to better understand the evolutionary dynamics of selection for resistance. We suggest approaches to increase the application of evolutionary-thinking to herbicide resistance research. Weed population dynamics models are increasingly important tools in weed management, yet these models often ignore intrapopulation and interpopulation variability, neglecting the potential for weed adaptation in response to management. Future agricultural weed management can benefit from greater integration of ecological and evolutionary principles to predict the long-term responses of weed populations to changing weed management, agricultural environments and global climate.

Fitness costs associated with evolved herbicide resistance alleles in plants

Predictions based on evolutionary theory suggest that the adaptive value of evolved herbicide resistance alleles may be compromised by the existence of fitness costs. There have been many studies quantifying the fitness costs associated with novel herbicide resistance alleles, reflecting the importance of fitness costs in determining the evolutionary dynamics of resistance. However, many of these studies have incorrectly defined resistance or used inappropriate plant material and methods to measure fitness. This review has two major objectives. First, to propose a methodological framework that establishes experimental criteria to unequivocally evaluate fitness costs. Second, to present a comprehensive analysis of the literature on fitness costs associated with herbicide resistance alleles. This analysis reveals unquestionable evidence that some herbicide resistance alleles are associated with pleiotropic effects that result in plant fitness costs. Observed costs are evident from herbicide resistance-endowing amino acid substitutions in proteins involved in amino acid, fatty acid, auxin and cellulose biosynthesis, as well as enzymes involved in herbicide metabolism. However, these resistance fitness costs are not universal and their expression depends on particular plant alleles and mutations. The findings of this review are discussed within the context of the plant defence trade-off theory and herbicide resistance evolution.

Gene flow, invasiveness, and ecological impact of genetically modified crops

The main environmental concerns about genetically modified (GM) crops are the potential weediness or invasiveness in the crop itself or in its wild or weedy relatives as a result of transgene movement. Here we briefly review evidence for pollen- and seed-mediated gene flow from GM crops to non-GM or other GM crops and to wild relatives. The report focuses on the effect of abiotic and biotic stress-tolerance traits on plant fitness and their potential to increase weedy or invasive tendencies. An evaluation of weediness and invasive traits that contribute to the success of agricultural weeds and invasive plants was of limited value in predicting the effect of biotic and abiotic stress-tolerance GM traits, suggesting context-specific evaluation rather than generalizations. Fitness data on herbicide, insect, and disease resistance, as well as cold-, drought-, and salinity-tolerance traits, are reviewed. We describe useful ecological models predicting the effects of gene flow and altered fitness in GM crops and wild/weedy relatives, as well as suitable mitigation measures. A better understanding of factors controlling population size, dynamics, and range limits in weedy volunteer GM crop and related host or target weed populations is necessary before the effect of biotic and abiotic stress-tolerance GM traits can be fully assessed.

Modelling binary mixtures of herbicides in populations resistant to one of the components: evaluation for resistance management

BACKGROUND

Herbicide mixtures are commonly proposed to delay the selection of herbicide resistance in susceptible populations (called the SM strategy). However, in practice, herbicide mixtures are often used when resistance to one of the two active ingredients has already been detected in the targeted population (called the RM strategy). It is doubtful whether such a practice can select against resistance, as the corresponding selection pressure is still exerted. As a consequence, the effect of mixtures on the evolution of an already detected resistance to one of the herbicides in the combination remains largely unexplored. In the present work, a simple model was developed to explore further the necessary and sufficient conditions under which a binary RM strategy might stabilise or even reduce resistance frequency.

RESULTS

Covering the hypothetical largest range of parameters, 39% of 9000 random simulations attest that the RM strategy might theoretically reduce resistance frequency. When strong enough, high genetic cost of resistance, negative cross-resistance between the herbicides associated in the mixture and reduced selection differential between resistant and susceptible plants can counterbalance the resistance advantage to one of the two applied herbicides. However, the required conditions for an RM strategy to ensure resistance containment in natural conditions seldom overlap with experimental parameter estimates given in the literature.

CONCLUSION

It is concluded that the sufficient conditions for an RM strategy to be effective would rarely be encountered. As a consequence, the strategy of formulating mixtures with herbicides for which resistance has already been detected should be avoided.

Clarification of pathway-specific inhibition by Fourier transform ion cyclotron resonance/mass spectrometry-based metabolic phenotyping studies

We have developed a metabolic profiling scheme based on direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS). The scheme consists of: (1) reproducible data collection under optimized FT-ICR/MS analytical conditions; (2) automatic mass-error correction and multivariate analyses for metabolome characterization using a newly developed metabolomics tool (DMASS software); (3) identification of marker metabolite candidates by searching a species-metabolite relationship database, KNApSAcK; and (4) structural analyses by an MS/MS method. The scheme was applied to metabolic phenotyping of Arabidopsis (Arabidopsis thaliana) seedlings treated with different herbicidal chemical classes for pathway-specific inhibitions. Arabidopsis extracts were directly infused into an electrospray ionization source on an FT-ICR/MS system. Acquired metabolomics data were comprised of mass-to-charge ratio values with ion intensity information subjected to principal component analysis, and metabolic phenotypes from the herbicide treatments were clearly differentiated from those of the herbicide-free treatment. From each herbicide treatment, candidate metabolites representing such metabolic phenotypes were found through the KNApSAcK database search. The database search and MS/MS analyses suggested dose-dependent accumulation patterns of specific metabolites including several flavonoid glycosides. The metabolic phenotyping scheme on the basis of FT-ICR/MS coupled with the DMASS program is discussed as a general tool for high throughput metabolic phenotyping studies.

Weed response to herbicides: regional-scale distribution of herbicide resistance alleles in the grass weed Alopecurus myosuroides

Effective herbicide resistance management requires an assessment of the range of spatial dispersion of resistance genes among weed populations and identification of the vectors of this dispersion. In the grass weed Alopecurus myosuroides (black-grass), seven alleles of the acetyl-CoA carboxylase (ACCase) gene are known to confer herbicide resistance. Here, we assessed their respective frequencies and spatial distribution on two nested geographical scales (the whole of France and the French administrative district of Côte d'Or) by genotyping 13 151 plants originating from 243 fields. Genetic variation in ACCase was structured in local populations at both geographical scales. No spatial structure in the distribution of resistant ACCase alleles and no isolation by distance were detected at either geographical scale investigated. These data, together with ACCase sequencing and data from the literature, suggest that evolution of A. myosuroides resistance to herbicides occurred at the level of the field or group of adjacent fields by multiple, independent appearances of mutant ACCase alleles that seem to have rather restricted spatial propagation. Seed transportation by farm machinery seems the most likely vector for resistance gene dispersal in A. myosuroides.