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Penicillium digitatum is a widespread pathogen responsible for the postharvest decay of citrus, one of the most economically important crops worldwide. Currently, chemical fungicides are still the main strategy to control the green mould disease caused by the fungus. However, the increasing selection and proliferation of fungicide-resistant strains require more efforts to explore new alternatives acting via new or unexplored mechanisms for postharvest disease management. To date, several non-chemical compounds have been investigated for the control of fungal pathogens. In this scenario, understanding the molecular determinants underlying P. digitatum’s response to biological and chemical antifungals may help in the development of safer and more effective non-chemical control methods. In this work, a proteomic approach based on isobaric labelling and a nanoLC tandem mass spectrometry approach was used to investigate molecular changes associated with P. digitatum’s response to treatments with α-sarcin and beetin 27 (BE27), two proteins endowed with antifungal activity. The outcomes of treatments with these biological agents were then compared with those triggered by the commonly used chemical fungicide thiabendazole (TBZ). Our results showed that differentially expressed proteins mainly include cell wall-degrading enzymes, proteins involved in stress response, antioxidant and detoxification mechanisms and metabolic processes such as thiamine biosynthesis. Interestingly, specific modulations in response to protein toxins treatments were observed for a subset of proteins. Deciphering the inhibitory mechanisms of biofungicides and chemical compounds, together with understanding their effects on the fungal physiology, will provide a new direction for improving the efficacy of novel antifungal formulations and developing new control strategies.

international journal of molecular sciences

Deciphering Molecular Determinants Underlying Penicillium digitatum’s Response to Biological and Chemical Antifungal Agents by Tandem Mass Tag (TMT)-Based High-Resolution LC-MS/MS