Modeling the Secondary Metabolism of the Penicillium Genus

Production of pharmaceutically relevant secondary metabolites (SMs) is a characteristic of Penicillium species, which has formed the foundation for a lot of research within the genus. The beneficial effects of these compounds have been industrially exploited for decades with penicillin antibiotics being the prime example. Production, however, is often limited by low yields, which historically have been overcome by classical strain engineering. Using genome-scale metabolic models (GEMs) to understand the metabolic fluxes governing SM production might however, provide suggestions to rationale metabolic engineering strategies leading to improved production performance.

In this project, batch cultivations were performed in bioreactors with 7 Penicillium spp. under SM inducing conditions (complex medium) and under conditions known to facilitate little SM formation (defined medium). Physiological characteristics were determined (growth rates and yields) and the secondary metabolite profiles were identified by LC-MS. Indeed, the LC-MS data showed a considerable greater SM induction in the complex medium compared to the defined medium, in terms of number of detected compounds. Some of these could be identified as specific SMs with known antimicrobial activity. The cultivated strains were, moreover subject to whole genome sequencing connected to an assembly and annotation pipeline. Based on the annotated genomes, the metabolic networks were reconstructed using the Penicillium chrysogenum model, iAL1006, as template. The reconstruction had particular emphasis on refining the secondary metabolism and including SM producing pathways to the model.

Future work will focus on integrating transcriptome data and the experimental constraints in the model, in order to compare the metabolism under normal and SM inducing conditions.