Insights into optimization of oleaginous fungi – genome-scale metabolic reconstruction and analysis of Umbelopsis sp. WA50703

Oleaginous fungi-known for their high lipid content of up to 80 % of dry mass-are of significant interest for biotechnological applications, particularly in biofuel and fatty acid production. Among these, the genus <i>Umbelopsis</i>, a common soil saprotroph of the Mucoromycota phylum, stands out for its rapid growth, low nutritional requirements, and ability to produce substantial amounts of lipids, especially polyunsaturated fatty acids (PUFAs). Despite previous studies on lipid production in <i>Umbelopsis</i>, metabolic engineering has been underexplored. This study fills that gap by presenting the first comprehensive metabolic model for <i>Umbelopsis</i> sp. WA50703, encompassing 2418 metabolites, 2215 reactions, and 1627 genes (iUmbe1). The model demonstrated a strong predictive accuracy correctly predicting metabolic capabilities in 81.05 % of cases when evaluated against experimental data. The Flux Scanning based on Enforced Objective Flux (FSEOF) algorithm was utilized to identify gene targets for enhancing lipid production. This analysis revealed 33 genes associated with 23 metabolic reactions relevant to lipid biosynthesis. Notably, the reactions catalysed by acetyl-CoA carboxylase and carbonic anhydrase emerged as prime candidates for up-regulation. These findings provide clear guidelines for future metabolic engineering efforts to optimize PUFA production in <i>Umbelopsis</i> strains.