Pseudomonas aeruginosa and Aspergillus fumigatus are pathogens frequently co-inhabiting immunocompromised patient airways, particularly in people with cystic fibrosis. Both microbes depend on the availability of iron, and compete for iron in their microenvironment. We showed previously that the P . aeruginosa siderophore pyoverdine is the main instrument in battling A . fumigatus biofilms, by iron chelation and denial of iron to the fungus. Here we show that A . fumigatus siderophores defend against anti-fungal P . aeruginosa effects. P . aeruginosa supernatants produced in the presence of wildtype A . fumigatus planktonic supernatants (Afsup) showed less activity against A . fumigatus biofilms than P . aeruginosa supernatants without Afsup, despite higher production of pyoverdine by P . aeruginosa . Supernatants of A . fumigatus cultures lacking the sidA gene (AfΔ sidA ), unable to produce hydroxamate siderophores, were less capable of protecting A . fumigatus biofilms from P . aeruginosa supernatants and pyoverdine. AfΔ sidA biofilm was more sensitive towards inhibitory effects of pyoverdine, the iron chelator deferiprone (DFP), or amphothericin B than wildtype A . fumigatus biofilm. Supplementation of sidA -deficient A . fumigatus biofilm with A . fumigatus siderophores restored resistance to pyoverdine. The A. fumigatus siderophore production inhibitor celastrol sensitized wildtype A . fumigatus biofilms towards the anti-fungal activity of DFP. In conclusion, A . fumigatus hydroxamate siderophores play a pivotal role in A . fumigatus competition for iron against P . aeruginosa .

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New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness (“hubs”), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.