Reconstruction of a Context-Specific Model Based on Genome-Scale Metabolic Simulation for Identification of Prochloraz Resistance Mechanisms in Penicillium digitatum

Abstract

Penicillium digitatum is the most destructive postharvest pathogen of citrus fruits, causing substantial economic losses. Prochloraz-resistant strains have emerged due to overuse of imidazole fungicides in agriculture. To study the prochloraz resistance mechanisms at the system level, a genome-scale metabolic model (GEM, iPD1512) of P. digitatum was reconstructed and constrained based on context-specific transcriptome data of the prochloraz-resistant strain, PdF6, from our previous work, a newly sequenced, context-specific transcriptome result of the major facilitator superfamily transporter-encoding gene mfs2 knockout mutant PdF6Δmfs2, and experimentally derived growth rate data. Through the model, iPD1512, the processes of prochloraz resistance in P. digitatum were well simulated. In detail, the growth rates of both wild-type and mutant P. digitatum under different prochloraz concentrations were simulated using constraint-based reconstruction and analysis. The growth rates of the mutant strains (sterol regulatory element-binding protein-encoding gene sreA knockout mutant PdF6ΔsreA and PdF6Δmfs2) were calculated and confirmed to be consistent with the simulation results. Furthermore, correlations between genes and prochloraz resistance were predicted and showed a great difference when compared with correlation results based on p-values from the hypothesis testing used by comparative transcriptomics. To sum up, in contrast to traditional transcriptome analysis, the GEM provides a systemic and dynamic drug resistance mechanism, which might help to detect some key upstream regulatory genes, but with small expression changes, and might provide more efficient targets to control prochloraz-resistant P. digitatum.