Genome-scale metabolic modelling of the priority fungal pathogen Lichtheimia corymbifera

Fungi harbor unique primary and secondary metabolic pathways that represent a hidden treasure of biochemical and natural compounds. Their metabolism is central to their ability to interact with, to adapt to and to survive in host environments, and to cause human disease and great harm. Among these is Lichtheimia corymbifera, an emerging causative agent of mucormycosis that has been classified as high priority fungal pathogen by the World Health Organization and is gaining increasing importance as a model organism for research on invasive fungal infections. We reconstructed a genome-scale L. corymbifera metabolic model and show substantial differential metabolic activity to process carbohydrate or amino acid carbon sources. We furthermore adapt the model to proteome changes depending on the presence of human peripheral blood mononuclear cells (PBMCs) and show fungal sphingolipid metabolic activity changes next to changes in cytoskeleton and tight junction associated PBMC activity over three days of cultivation. These insights underline the possibility that L. corymbifera can potentially scavenge host-derived lipids to fortify its own cell membrane. We demonstrate that in silico metabolic predictions can provide testable hypotheses and can lead to the identification of metabolic processes which are essential for the development of targeted antifungal drugs and novel solutions for balancing host challenges.