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Oleaginous fungi, known for their high lipid content—up to 80% of their dry mass—are of significant interest for biotechnological applications, particularly in biofuel and fatty acid production. Among these, the genus Umbelopsis, 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 Umbelopsis, metabolic engineering has been underexplored. This study fills that gap by presenting the first comprehensive metabolic model for Umbelopsis sp. WA50703, encompassing 2413 metabolites, 2216 reactions, and 1629 genes (iUmbe1). The model demonstrated strong predictive accuracy, correctly predicting metabolic capabilities in 82.1% of cases when evaluated against experimental data. Using the Flux Scanning based on Enforced Objective Flux (FSEOF) algorithm, the study identified 33 genes linked to 23 metabolic reactions. Notably, reactions catalysed by acetyl-CoA carboxylase and carbonic anhydrase emerged as prime candidates for up-regulation. These findings provide a solid framework for future metabolic engineering efforts to optimize PUFA production in Umbelopsis strains.
Dziurzyński, M., Nowak, M. E., Furman, M., Okrasińska, A., Pawłowska, J., & Fondi, M. Insights into optimization of oleaginous fungi – genome-scale metabolic reconstruction and analysis of Umbelopsis sp. WA50703. bioRxiv. doi:https://doi.org/10.1101/2024.10.01.616082
Metabolic modeling; Lipid synthesis; Biotechnology; Filamentous fungi; Fatty acids
Utilisation: experimental data reconstruction; multi-omics integrative analysis; in silico strain design; model template
Field: metabolic-network reconstruction
Type of model: reconstruction; curated
Omic source: genomics; transcriptomics, phenomics
Taxonomic name: Umbelopsis sp. WA50703
Taxonomy ID: taxonomy:3097288
Genome ID: insdc.gca:GCA_964291815.1
Metabolic system: general metabolism
Strain: WA50703
Condition: aerobic; minimal synthetic medium
The model can be read and analysed using COBRApy, a community-driven Python package for constraint-based modeling of metabolic networks.
import cobra
from cobra.io import read_sbml_model
model = read_sbml_model("iUmbe1.smbl")
model.optimize()
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