The Emergence of Resistance to Fungicides

Abstract

Many studies exist about the selection phase of fungicide resistance evolution, where a resistant strain is present in a pathogen population and is differentially selected for by the application of fungicides. The emergence phase of the evolution of fungicide resistance - where the resistant strain is not present in the population and has to arise through mutation and subsequently invade the population - has not been studied to date. Here, we derive a model which describes the emergence of resistance in pathogen populations of crops. There are several important examples where a single mutation, affecting binding of a fungicide with the target protein, shifts the sensitivity phenotype of the resistant strain to such an extent that it cannot be controlled effectively (‘qualitative’ or ‘single-step’ resistance). The model was parameterized for this scenario for Mycosphaerella graminicola on winter wheat and used to evaluate the effect of fungicide dose rate on the time to emergence of resistance for a range of mutation probabilities, fitness costs of resistance and sensitivity levels of the resistant strain. We also evaluated the usefulness of mixing two fungicides of differing modes of action for delaying the emergence of resistance. The results suggest that it is unlikely that a resistant strain will already have emerged when a fungicide with a new mode of action is introduced. Hence, ‘anti-emergence’ strategies should be identified and implemented. For all simulated scenarios, the median emergence time of a resistant strain was affected little by changing the dose rate applied, within the range of doses typically used on commercial crops. Mixing a single-site acting fungicide with a multi-site acting fungicide delayed the emergence of resistance to the single-site component. Combining the findings with previous work on the selection phase will enable us to develop more efficient anti-resistance strategies.

Fungicide resistance risk assessment based on traits associated with the rate of pathogen evolution

“…In spite of the improved predictive power of the new model, the 95% confidence intervals on predicted FDR time suggest a large degree of uncertainty surrounding risk predictions. This may be expected, as the emergence and invasion of a new pathogen strain is driven by stochastic processes such as the survival of resistant mutant individuals and the subsequent build‐up of a population of resistant lesions competing with a much larger wild‐type population …”

Resistência cruzada aos fungicidas IQo azoxistrobina e piraclostrobina no patógeno da brusone do trigo Pyricularia oryzae no Brasil

“…No caso de um elevado custo adaptativo associado com a aquisição de resistência IQo, com a remoção da pressão da seleção de fungicidas IQo, previa-se que as populações de P. oryzae poderiam retornar aos seus níveis originais de sensibilidade ao fungicida (10). Entretanto, as mutações para resistência relatadas para P. oryzae que infecta outras poáceas foram consideradas estáveis e sem custo adaptativo para o patógeno, indicando um cenário irreversível (13).…”

Transcription Factor ADS-4 Regulates Adaptive Responses and Resistance to Antifungal Azole Stress

“…ilamentous fungi cause over 70% of plant diseases, and some can cause deadly infections in humans (1)(2)(3)(4)(5). Azoles (e.g., itraconazole [ITA], fluconazole [FLC], and ketoconazole [KTC]) are the most commonly used antifungal drugs in medicine, and some azoles, such as triadimenol and propiconazole, are also used to control fungal diseases in plants (6).…”